Datasets:

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ftopal

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huggingface-datasets

like 0

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of ewqr2130/alignment-handbook-zephyr-7b_ppo_5e7step_102\n\n\n\nDataset automatically created during the evaluation run of model ewqr2130/alignment-handbook-zephyr-7b_ppo_5e7step_102 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-19T20:51:30.174111(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of ewqr2130/alignment-handbook-zephyr-7b_ppo_5e7step_102\n\n\n\nDataset automatically created during the evaluation run of model ewqr2130/alignment-handbook-zephyr-7b_ppo_5e7step_102 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-19T20:51:30.174111(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "license:mit", "region:us" ]

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[ "TAGS\n#license-mit #region-us \n" ]

[ "region:us" ]

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[ "# Dataset Card for \"fashion_image_caption-100-v2\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"fashion_image_caption-100-v2\"\n\nMore Information needed" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of ewqr2130/alignment-handbook-zephyr-7b-sft-full-dpo-5e7-cont2\n\n\n\nDataset automatically created during the evaluation run of model ewqr2130/alignment-handbook-zephyr-7b-sft-full-dpo-5e7-cont2 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-19T21:12:05.940031(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of ewqr2130/alignment-handbook-zephyr-7b-sft-full-dpo-5e7-cont2\n\n\n\nDataset automatically created during the evaluation run of model ewqr2130/alignment-handbook-zephyr-7b-sft-full-dpo-5e7-cont2 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-19T21:12:05.940031(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of AA051610/A0120\n\n\n\nDataset automatically created during the evaluation run of model AA051610/A0120 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-19T21:18:32.527803(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of AA051610/A0120\n\n\n\nDataset automatically created during the evaluation run of model AA051610/A0120 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-19T21:18:32.527803(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "Lilac", "region:us" ]

[]

[]

[ "# lilac/Capybara\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:" ]

[ "TAGS\n#Lilac #region-us \n", "# lilac/Capybara\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:" ]

[ "task_categories:translation", "size_categories:100K<n<1M", "language:fr", "language:en", "license:mit", "region:us" ]

[]

[ "fr", "en" ]

[ "# Anki-Global Voices English-French Translation Dataset", "## Description\n\nThe Anki-Global Voices English-French Translation Dataset is a comprehensive collection of over 500,000 translation pairs, merging the Anki English to French dataset with the Global Voices English to French dataset. This unique dataset provides a wide range of sentences, suitable for training and evaluating machine translation models in both informal and formal language contexts.", "### Languages\n\nThis dataset includes sentence pairs in English (ISO 639-1: EN) and French (ISO 639-1: FR).", "## Dataset Structure", "### Data Instances\n\nEach data instance consists of an English sentence and its French translation. Example:", "### Data Fields\n\n- 'source': The English sentence.\n- 'target': The corresponding French translation.", "### Data Splits\n\nThe dataset is divided into training, validation, and test sets. The distribution is as follows (illustrative numbers):\n\n- Train: 439,000 pairs\n- Validation: 54,900 pairs\n- Test: 54,900 pairs", "## Dataset Creation", "### Curation Rationale\n\nThis dataset aims to aid the development of machine translation models by providing a rich source of linguistic variations and expressions in English and French, covering both everyday language and formal contexts.", "### Source Data", "#### Initial Data Collection and Normalization\n\nThe dataset combines two sources:\n\n1. Anki English to French Dataset: Comprised of curated translation pairs submitted to the Tatoeba Project, mostly short and with casual language. More information\n2. Global Voices English to French Dataset: Derived from news and cultural articles on the Global Voices websites, featuring more formal, complicated language. More information\n\nApproximately 21,000 pairs were removed from the Global Voices dataset before merging with the Anki Dataset due to severe misalignment. Samples have already been shuffled.", "### Annotations\n\nThe dataset contains translations but no additional annotations.", "#### Annotation Process\n\nTranslations in the Anki dataset were community-contributed, and those in the Global Voices dataset were done by professional translators and journalists.", "### Personal and Sensitive Information\n\nThe dataset does not contain personal or sensitive information.", "## Considerations for Using the Data", "### Social Impact of Dataset\n\nThis dataset can help improve the accuracy of machine translation systems, facilitating communication across different language speakers.", "### Discussion of Biases\n\nThe dataset covers both informal and formal language contexts, providing a balanced linguistic range. However, source datasets' biases might be present.", "### Other Known Limitations\n\nThe dataset focuses exclusively on English-French translations, which may not generalize to other language pairs or cultural contexts.", "## Additional Information", "### Dataset Curators\n\nCurated by Ariel Guerra-Adames, this dataset combines the Anki and Global Voices datasets into a comprehensive resource for machine translation.", "### Licensing Information\n\nSee LICENSE" ]

[ "TAGS\n#task_categories-translation #size_categories-100K<n<1M #language-French #language-English #license-mit #region-us \n", "# Anki-Global Voices English-French Translation Dataset", "## Description\n\nThe Anki-Global Voices English-French Translation Dataset is a comprehensive collection of over 500,000 translation pairs, merging the Anki English to French dataset with the Global Voices English to French dataset. This unique dataset provides a wide range of sentences, suitable for training and evaluating machine translation models in both informal and formal language contexts.", "### Languages\n\nThis dataset includes sentence pairs in English (ISO 639-1: EN) and French (ISO 639-1: FR).", "## Dataset Structure", "### Data Instances\n\nEach data instance consists of an English sentence and its French translation. Example:", "### Data Fields\n\n- 'source': The English sentence.\n- 'target': The corresponding French translation.", "### Data Splits\n\nThe dataset is divided into training, validation, and test sets. The distribution is as follows (illustrative numbers):\n\n- Train: 439,000 pairs\n- Validation: 54,900 pairs\n- Test: 54,900 pairs", "## Dataset Creation", "### Curation Rationale\n\nThis dataset aims to aid the development of machine translation models by providing a rich source of linguistic variations and expressions in English and French, covering both everyday language and formal contexts.", "### Source Data", "#### Initial Data Collection and Normalization\n\nThe dataset combines two sources:\n\n1. Anki English to French Dataset: Comprised of curated translation pairs submitted to the Tatoeba Project, mostly short and with casual language. More information\n2. Global Voices English to French Dataset: Derived from news and cultural articles on the Global Voices websites, featuring more formal, complicated language. More information\n\nApproximately 21,000 pairs were removed from the Global Voices dataset before merging with the Anki Dataset due to severe misalignment. Samples have already been shuffled.", "### Annotations\n\nThe dataset contains translations but no additional annotations.", "#### Annotation Process\n\nTranslations in the Anki dataset were community-contributed, and those in the Global Voices dataset were done by professional translators and journalists.", "### Personal and Sensitive Information\n\nThe dataset does not contain personal or sensitive information.", "## Considerations for Using the Data", "### Social Impact of Dataset\n\nThis dataset can help improve the accuracy of machine translation systems, facilitating communication across different language speakers.", "### Discussion of Biases\n\nThe dataset covers both informal and formal language contexts, providing a balanced linguistic range. However, source datasets' biases might be present.", "### Other Known Limitations\n\nThe dataset focuses exclusively on English-French translations, which may not generalize to other language pairs or cultural contexts.", "## Additional Information", "### Dataset Curators\n\nCurated by Ariel Guerra-Adames, this dataset combines the Anki and Global Voices datasets into a comprehensive resource for machine translation.", "### Licensing Information\n\nSee LICENSE" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of freecs/ThetaWave-7B-v1\n\n\n\nDataset automatically created during the evaluation run of model freecs/ThetaWave-7B-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-19T21:50:23.328123(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of freecs/ThetaWave-7B-v1\n\n\n\nDataset automatically created during the evaluation run of model freecs/ThetaWave-7B-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-19T21:50:23.328123(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "size_categories:n<1K", "doi:10.57967/hf/1672", "region:us" ]

[]

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[ "# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#size_categories-n<1K #doi-10.57967/hf/1672 #region-us \n", "# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

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[ "# Dataset Card for \"Instance_Seg_DB\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"Instance_Seg_DB\"\n\nMore Information needed" ]

[ "region:us" ]

[]

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[ "# Dataset Card for \"New_Instance_Seg_DB\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"New_Instance_Seg_DB\"\n\nMore Information needed" ]

[ "region:us" ]

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[]

[ "# Dataset Card for Evaluation run of soniox/Soniox-7B-v1.0\n\n\n\nDataset automatically created during the evaluation run of model soniox/Soniox-7B-v1.0 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-19T23:00:10.357078(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of soniox/Soniox-7B-v1.0\n\n\n\nDataset automatically created during the evaluation run of model soniox/Soniox-7B-v1.0 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-19T23:00:10.357078(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:object-detection", "language:en", "license:cc-by-4.0", "agriculture", "biology", "arxiv:2105.07660", "region:us" ]

[ "2105.07660" ]

[ "en" ]

[ "# Dataset Card for \"Global Wheat Head Dataset 2021\" \n\nIf you want any update on the Global Wheat Dataset Community, go on URL", "## Table of Contents\n- Dataset Description\n- Dataset Composition\n- Usage\n- Citation\n- Acknowledgements", "## Dataset Description\n\n- Creators: Etienne David and others\n- Published: July 12, 2021 | Version 1.0\n- Availability: Zenodo Link\n- Keywords: Deep Learning, Wheat Counting, Plant Phenotyping", "### Introduction\nWheat is essential for a large part of humanity. The \"Global Wheat Head Dataset 2021\" aims to support the development of deep learning models for wheat head detection. This dataset addresses challenges like overlapping plants and varying conditions across global wheat fields. It's a step towards automating plant phenotyping and enhancing agricultural practices.", "### Dataset Composition\n- Images: Over 6000, Resolution - 1024x1024 pixels\n- Annotations: 300k+ unique wheat heads with bounding boxes\n- Geographic Coverage: Images from 11 countries\n- Domains: Various, including sensor types and locations\n- Splits: Training (Europe & Canada), Test (Other regions)", "## Dataset Composition", "### Files and Structure\n- Images: Folder containing all images ('.png')\n- CSV Files: 'competition_train.csv', 'competition_val.csv', 'competition_test.csv' for different dataset splits\n- Metadata: 'URL' with additional details", "### Labels\n- Format: CSV with columns - image_name, BoxesString, domain\n- BoxesString: '[x_min,y_min, x_max,y_max]' format for bounding boxes\n- Domain: Specifies the image domain", "## Usage", "### Tutorials and Resources\n- Tutorials available at AIcrowd Challenge Page", "### License\n- Type: Creative Commons Attribution 4.0 International (cc-by-4.0)\n- Details: Free to use with attribution\n\nIf you use this dataset in your research, please cite the following:", "## Acknowledgements\n\nSpecial thanks to all the contributors, researchers, and institutions that played a pivotal role in the creation of this dataset. Your efforts are helping to advance the field of agricultural sciences and technology." ]

[ "TAGS\n#task_categories-object-detection #language-English #license-cc-by-4.0 #agriculture #biology #arxiv-2105.07660 #region-us \n", "# Dataset Card for \"Global Wheat Head Dataset 2021\" \n\nIf you want any update on the Global Wheat Dataset Community, go on URL", "## Table of Contents\n- Dataset Description\n- Dataset Composition\n- Usage\n- Citation\n- Acknowledgements", "## Dataset Description\n\n- Creators: Etienne David and others\n- Published: July 12, 2021 | Version 1.0\n- Availability: Zenodo Link\n- Keywords: Deep Learning, Wheat Counting, Plant Phenotyping", "### Introduction\nWheat is essential for a large part of humanity. The \"Global Wheat Head Dataset 2021\" aims to support the development of deep learning models for wheat head detection. This dataset addresses challenges like overlapping plants and varying conditions across global wheat fields. It's a step towards automating plant phenotyping and enhancing agricultural practices.", "### Dataset Composition\n- Images: Over 6000, Resolution - 1024x1024 pixels\n- Annotations: 300k+ unique wheat heads with bounding boxes\n- Geographic Coverage: Images from 11 countries\n- Domains: Various, including sensor types and locations\n- Splits: Training (Europe & Canada), Test (Other regions)", "## Dataset Composition", "### Files and Structure\n- Images: Folder containing all images ('.png')\n- CSV Files: 'competition_train.csv', 'competition_val.csv', 'competition_test.csv' for different dataset splits\n- Metadata: 'URL' with additional details", "### Labels\n- Format: CSV with columns - image_name, BoxesString, domain\n- BoxesString: '[x_min,y_min, x_max,y_max]' format for bounding boxes\n- Domain: Specifies the image domain", "## Usage", "### Tutorials and Resources\n- Tutorials available at AIcrowd Challenge Page", "### License\n- Type: Creative Commons Attribution 4.0 International (cc-by-4.0)\n- Details: Free to use with attribution\n\nIf you use this dataset in your research, please cite the following:", "## Acknowledgements\n\nSpecial thanks to all the contributors, researchers, and institutions that played a pivotal role in the creation of this dataset. Your efforts are helping to advance the field of agricultural sciences and technology." ]

[ "source_datasets:starfishmedical/webGPT_x_dolly", "license:cc-by-sa-3.0", "region:us" ]

[]

[]

[]

[ "TAGS\n#source_datasets-starfishmedical/webGPT_x_dolly #license-cc-by-sa-3.0 #region-us \n" ]

[ "region:us" ]

[]

[]

[]

[ "TAGS\n#region-us \n" ]

[ "source_datasets:euclaise/reddit-instruct", "license:mit", "region:us" ]

[]

[]

[]

[ "TAGS\n#source_datasets-euclaise/reddit-instruct #license-mit #region-us \n" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:conversational", "size_categories:10K<n<100K", "language:ja", "license:llama2", "region:us" ]

[]

[ "ja" ]

[ "# Model\nURL", "# Dataset\nURL", "# Compute by\nTsuginosuke AI SuperComputer\nFreeAI Ltd.\n\nURL" ]

[ "TAGS\n#task_categories-conversational #size_categories-10K<n<100K #language-Japanese #license-llama2 #region-us \n", "# Model\nURL", "# Dataset\nURL", "# Compute by\nTsuginosuke AI SuperComputer\nFreeAI Ltd.\n\nURL" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of sonthenguyen/NeuralHermes-2.5-Mistral-7B\n\n\n\nDataset automatically created during the evaluation run of model sonthenguyen/NeuralHermes-2.5-Mistral-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T01:20:50.595952(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of sonthenguyen/NeuralHermes-2.5-Mistral-7B\n\n\n\nDataset automatically created during the evaluation run of model sonthenguyen/NeuralHermes-2.5-Mistral-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T01:20:50.595952(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:text-generation", "task_ids:parsing", "size_categories:100K<n<1M", "size_categories:1M<n<10M", "license:other", "python-copilot", "python-coding", "fine-tuning", "training", "alpaca", "text", "coding", "region:us" ]

[]

[]

[ "## Python Copilot Large Coding Dataset\n\nThis dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.", "### Details\n\nEach row contains python code, either a class method or a global function, imported modules, base classes (if any), exceptions (ordered based off the code), returns (ordered based off the code), arguments (ordered based off the code), and more.\n\n- Rows: 2350782\n- Size: 3.1 GB\n- Data type: text\n- Format: Extracted code using python AST", "### Schema", "### How to use the dataset" ]

[ "TAGS\n#task_categories-text-generation #task_ids-parsing #size_categories-100K<n<1M #size_categories-1M<n<10M #license-other #python-copilot #python-coding #fine-tuning #training #alpaca #text #coding #region-us \n", "## Python Copilot Large Coding Dataset\n\nThis dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.", "### Details\n\nEach row contains python code, either a class method or a global function, imported modules, base classes (if any), exceptions (ordered based off the code), returns (ordered based off the code), arguments (ordered based off the code), and more.\n\n- Rows: 2350782\n- Size: 3.1 GB\n- Data type: text\n- Format: Extracted code using python AST", "### Schema", "### How to use the dataset" ]

[ "task_categories:text-to-image", "task_categories:image-to-image", "task_categories:question-answering", "task_ids:parsing", "size_categories:100K<n<1M", "license:other", "python-copilot", "python-coding", "python-architecture", "knowledge-graphs", "multimodal", "text-image-audio", "fine-tuning", "training", "question-answering", "image-knowledge-graph", "alpaca", "mp3", "png", "text", "instruct", "class", "classes", "region:us" ]

[]

[]

[ "## Python Copilot Image Training using Class Knowledge Graphs\n\nThis dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.", "### Details\n\nEach row contains a png file in the dbytes column.\n\n- Rows: 312277\n- Size: 304.3 GB\n- Data type: png\n- Format: Knowledge graph using NetworkX with alpaca text box", "### Schema\n\nThe png is in the dbytes column:", "### How to use the dataset" ]

[ "TAGS\n#task_categories-text-to-image #task_categories-image-to-image #task_categories-question-answering #task_ids-parsing #size_categories-100K<n<1M #license-other #python-copilot #python-coding #python-architecture #knowledge-graphs #multimodal #text-image-audio #fine-tuning #training #question-answering #image-knowledge-graph #alpaca #mp3 #png #text #instruct #class #classes #region-us \n", "## Python Copilot Image Training using Class Knowledge Graphs\n\nThis dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.", "### Details\n\nEach row contains a png file in the dbytes column.\n\n- Rows: 312277\n- Size: 304.3 GB\n- Data type: png\n- Format: Knowledge graph using NetworkX with alpaca text box", "### Schema\n\nThe png is in the dbytes column:", "### How to use the dataset" ]

[ "task_categories:text-to-image", "task_categories:image-to-image", "task_categories:question-answering", "task_ids:parsing", "size_categories:100K<n<1M", "license:other", "python-copilot", "python-coding", "python-architecture", "knowledge-graphs", "multimodal", "text-image-audio", "fine-tuning", "training", "question-answering", "image-knowledge-graph", "alpaca", "mp3", "png", "text", "instruct", "function", "functions", "region:us" ]

[]

[]

[ "## Python Copilot Image Training using Function Knowledge Graphs\n\nThis dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.", "### Details\n\nEach row contains a png file in the dbytes column.\n\n- Rows: 134357\n- Size: 130.5 GB\n- Data type: png\n- Format: Knowledge graph using NetworkX with alpaca text box", "### Schema\n\nThe png is in the dbytes column:", "### How to use the dataset" ]

[ "TAGS\n#task_categories-text-to-image #task_categories-image-to-image #task_categories-question-answering #task_ids-parsing #size_categories-100K<n<1M #license-other #python-copilot #python-coding #python-architecture #knowledge-graphs #multimodal #text-image-audio #fine-tuning #training #question-answering #image-knowledge-graph #alpaca #mp3 #png #text #instruct #function #functions #region-us \n", "## Python Copilot Image Training using Function Knowledge Graphs\n\nThis dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.", "### Details\n\nEach row contains a png file in the dbytes column.\n\n- Rows: 134357\n- Size: 130.5 GB\n- Data type: png\n- Format: Knowledge graph using NetworkX with alpaca text box", "### Schema\n\nThe png is in the dbytes column:", "### How to use the dataset" ]

[ "task_categories:text-to-image", "task_categories:image-to-image", "task_categories:question-answering", "task_ids:parsing", "size_categories:100K<n<1M", "license:other", "python-copilot", "python-coding", "python-architecture", "knowledge-graphs", "multimodal", "text-image-audio", "fine-tuning", "training", "question-answering", "image-knowledge-graph", "alpaca", "mp3", "png", "text", "instruct", "base_class", "base_classes", "inheritance", "polymorphism", "region:us" ]

[]

[]

[ "## Python Copilot Image Training using Inheritance and Polymorphism Knowledge Graphs\n\nThis dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.", "### Details\n\nEach row contains a png file in the dbytes column.\n\n- Rows: 259017\n- Size: 135.2 GB\n- Data type: png\n- Format: Knowledge graph using NetworkX with alpaca text box", "### Schema\n\nThe png is in the dbytes column:", "### How to use the dataset" ]

[ "TAGS\n#task_categories-text-to-image #task_categories-image-to-image #task_categories-question-answering #task_ids-parsing #size_categories-100K<n<1M #license-other #python-copilot #python-coding #python-architecture #knowledge-graphs #multimodal #text-image-audio #fine-tuning #training #question-answering #image-knowledge-graph #alpaca #mp3 #png #text #instruct #base_class #base_classes #inheritance #polymorphism #region-us \n", "## Python Copilot Image Training using Inheritance and Polymorphism Knowledge Graphs\n\nThis dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.", "### Details\n\nEach row contains a png file in the dbytes column.\n\n- Rows: 259017\n- Size: 135.2 GB\n- Data type: png\n- Format: Knowledge graph using NetworkX with alpaca text box", "### Schema\n\nThe png is in the dbytes column:", "### How to use the dataset" ]

[ "task_categories:text-to-audio", "task_categories:audio-to-audio", "task_categories:question-answering", "task_ids:parsing", "size_categories:100K<n<1M", "license:other", "python-copilot", "python-coding", "python-architecture", "knowledge-graphs", "multimodal", "text-image-audio", "fine-tuning", "training", "question-answering", "image-knowledge-graph", "alpaca", "mp3", "png", "text", "instruct", "class", "classes", "region:us" ]

[]

[]

[ "## Python Copilot Audio Training using Class with Knowledge Graphs\n\nThis dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.", "### Details\n\nEach class method has a question and answer mp3 where one voice reads the question and another voice reads the answer. Both mp3s are stored in the parquet dbytes column and the associated source code file_path identifier.\n\n- Rows: 211020\n- Size: 95.3 GB\n- Data type: mp3\n- Format: narrated alpaca question and answers using two voices", "### Schema", "### How to use the dataset" ]

[ "TAGS\n#task_categories-text-to-audio #task_categories-audio-to-audio #task_categories-question-answering #task_ids-parsing #size_categories-100K<n<1M #license-other #python-copilot #python-coding #python-architecture #knowledge-graphs #multimodal #text-image-audio #fine-tuning #training #question-answering #image-knowledge-graph #alpaca #mp3 #png #text #instruct #class #classes #region-us \n", "## Python Copilot Audio Training using Class with Knowledge Graphs\n\nThis dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.", "### Details\n\nEach class method has a question and answer mp3 where one voice reads the question and another voice reads the answer. Both mp3s are stored in the parquet dbytes column and the associated source code file_path identifier.\n\n- Rows: 211020\n- Size: 95.3 GB\n- Data type: mp3\n- Format: narrated alpaca question and answers using two voices", "### Schema", "### How to use the dataset" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of KnutJaegersberg/Qwen-1_8B-Chat-llama\n\n\n\nDataset automatically created during the evaluation run of model KnutJaegersberg/Qwen-1_8B-Chat-llama on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T02:47:07.832828(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of KnutJaegersberg/Qwen-1_8B-Chat-llama\n\n\n\nDataset automatically created during the evaluation run of model KnutJaegersberg/Qwen-1_8B-Chat-llama on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T02:47:07.832828(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of RatanRohith/NeuralMathChat-7B-V0.2\n\n\n\nDataset automatically created during the evaluation run of model RatanRohith/NeuralMathChat-7B-V0.2 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T02:57:06.316295(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of RatanRohith/NeuralMathChat-7B-V0.2\n\n\n\nDataset automatically created during the evaluation run of model RatanRohith/NeuralMathChat-7B-V0.2 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T02:57:06.316295(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of 222gate/BrurryDog-7b-v0.1\n\n\n\nDataset automatically created during the evaluation run of model 222gate/BrurryDog-7b-v0.1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T03:26:36.549937(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of 222gate/BrurryDog-7b-v0.1\n\n\n\nDataset automatically created during the evaluation run of model 222gate/BrurryDog-7b-v0.1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T03:26:36.549937(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "language:ja", "license:cc-by-4.0", "arxiv:2004.06063", "arxiv:2305.18290", "region:us" ]

[ "2004.06063", "2305.18290" ]

[ "ja" ]

[ "### ELYZA-tasks-100 (GPT-4 eval)", "### Japanese MT-Bench\n\n\ncalm2-7b-chat: MEAN, calm2-7b-chat-dpo: 6.1\ncalm2-7b-chat: extraction, calm2-7b-chat-dpo: 4.1\ncalm2-7b-chat: humanities, calm2-7b-chat-dpo: 8.2\ncalm2-7b-chat: reasoning, calm2-7b-chat-dpo: 3.9\ncalm2-7b-chat: roleplay, calm2-7b-chat-dpo: 6.4\ncalm2-7b-chat: stem, calm2-7b-chat-dpo: 6.3\ncalm2-7b-chat: writing, calm2-7b-chat-dpo: 7.7\n\n\nDisclaimers and Terms\n---------------------\n\n\n* This dataset contains conversations that may be considered unsafe,\noffensive, or upsetting. It is not intended for training dialogue agents\nwithout applying appropriate filtering measures. We are not responsible for\nany outputs of the models trained on this dataset.\n* Statements or opinions made in this dataset do not reflect the views of\nresearchers or institutions involved in the data collection effort.\n* Users of this data are responsible for ensuring its appropriate use, which\nincludes abiding by any applicable laws and regulations.\n* Users of this data should adhere to the terms of use for a specific model\nwhen using its direct outputs.\n* Users of this data agree to not attempt to determine the identity of\nindividuals in this dataset.\n* このデータセットはキュレーションを行っておりません。重複した入力や出力が含まれます。\n\n\nReleases\n--------\n\n\n1.0: v1 release (Jan 24, 2024)\n\n\nAuthor\n------\n\n\nYuu Jinnai (jinnai\\_yu@URL), Standing on the shoulders of giants" ]

[ "TAGS\n#language-Japanese #license-cc-by-4.0 #arxiv-2004.06063 #arxiv-2305.18290 #region-us \n", "### ELYZA-tasks-100 (GPT-4 eval)", "### Japanese MT-Bench\n\n\ncalm2-7b-chat: MEAN, calm2-7b-chat-dpo: 6.1\ncalm2-7b-chat: extraction, calm2-7b-chat-dpo: 4.1\ncalm2-7b-chat: humanities, calm2-7b-chat-dpo: 8.2\ncalm2-7b-chat: reasoning, calm2-7b-chat-dpo: 3.9\ncalm2-7b-chat: roleplay, calm2-7b-chat-dpo: 6.4\ncalm2-7b-chat: stem, calm2-7b-chat-dpo: 6.3\ncalm2-7b-chat: writing, calm2-7b-chat-dpo: 7.7\n\n\nDisclaimers and Terms\n---------------------\n\n\n* This dataset contains conversations that may be considered unsafe,\noffensive, or upsetting. It is not intended for training dialogue agents\nwithout applying appropriate filtering measures. We are not responsible for\nany outputs of the models trained on this dataset.\n* Statements or opinions made in this dataset do not reflect the views of\nresearchers or institutions involved in the data collection effort.\n* Users of this data are responsible for ensuring its appropriate use, which\nincludes abiding by any applicable laws and regulations.\n* Users of this data should adhere to the terms of use for a specific model\nwhen using its direct outputs.\n* Users of this data agree to not attempt to determine the identity of\nindividuals in this dataset.\n* このデータセットはキュレーションを行っておりません。重複した入力や出力が含まれます。\n\n\nReleases\n--------\n\n\n1.0: v1 release (Jan 24, 2024)\n\n\nAuthor\n------\n\n\nYuu Jinnai (jinnai\\_yu@URL), Standing on the shoulders of giants" ]

[ "language:en", "region:us" ]

[]

[ "en" ]

[ "# Summary\n- wikipedia page : URL\n- Number of Politicians : 110\n- Null Images of Politicians : 16\n\n- link to dataset : URL\n- date of creation: 2024-20-01" ]

[ "TAGS\n#language-English #region-us \n", "# Summary\n- wikipedia page : URL\n- Number of Politicians : 110\n- Null Images of Politicians : 16\n\n- link to dataset : URL\n- date of creation: 2024-20-01" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of bartowski/internlm2-chat-20b-llama\n\n\n\nDataset automatically created during the evaluation run of model bartowski/internlm2-chat-20b-llama on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T04:32:43.004960(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of bartowski/internlm2-chat-20b-llama\n\n\n\nDataset automatically created during the evaluation run of model bartowski/internlm2-chat-20b-llama on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T04:32:43.004960(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of Epiculous/Fett-uccine-7B\n\n\n\nDataset automatically created during the evaluation run of model Epiculous/Fett-uccine-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T05:02:15.433939(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of Epiculous/Fett-uccine-7B\n\n\n\nDataset automatically created during the evaluation run of model Epiculous/Fett-uccine-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T05:02:15.433939(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of UCLA-AGI/zephyr-7b-sft-full-SPIN-iter3\n\n\n\nDataset automatically created during the evaluation run of model UCLA-AGI/zephyr-7b-sft-full-SPIN-iter3 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T04:40:32.614362(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of UCLA-AGI/zephyr-7b-sft-full-SPIN-iter3\n\n\n\nDataset automatically created during the evaluation run of model UCLA-AGI/zephyr-7b-sft-full-SPIN-iter3 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T04:40:32.614362(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:text-to-image", "task_categories:image-to-image", "task_categories:question-answering", "task_ids:parsing", "size_categories:100K<n<1M", "license:other", "python-copilot", "python-coding", "python-architecture", "knowledge-graphs", "multimodal", "text-image-audio", "fine-tuning", "training", "question-answering", "image-knowledge-graph", "alpaca", "mp3", "png", "text", "instruct", "import", "imports", "region:us" ]

[]

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[ "## Python Copilot Image Training using Import Knowledge Graphs\n\nThis dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.", "### Details\n\nEach row contains a png file in the dbytes column.\n\n- Rows: 216642\n- Size: 211.2 GB\n- Data type: png\n- Format: Knowledge graph using NetworkX with alpaca text box", "### Schema\n\nThe png is in the dbytes column:", "### How to use the dataset" ]

[ "TAGS\n#task_categories-text-to-image #task_categories-image-to-image #task_categories-question-answering #task_ids-parsing #size_categories-100K<n<1M #license-other #python-copilot #python-coding #python-architecture #knowledge-graphs #multimodal #text-image-audio #fine-tuning #training #question-answering #image-knowledge-graph #alpaca #mp3 #png #text #instruct #import #imports #region-us \n", "## Python Copilot Image Training using Import Knowledge Graphs\n\nThis dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.", "### Details\n\nEach row contains a png file in the dbytes column.\n\n- Rows: 216642\n- Size: 211.2 GB\n- Data type: png\n- Format: Knowledge graph using NetworkX with alpaca text box", "### Schema\n\nThe png is in the dbytes column:", "### How to use the dataset" ]

[ "license:mit", "region:us" ]

[]

[]

[]

[ "TAGS\n#license-mit #region-us \n" ]

[ "region:us" ]

[]

[]

[]

[ "TAGS\n#region-us \n" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of KnutJaegersberg/Qwen-1_8b-EverythingLM\n\n\n\nDataset automatically created during the evaluation run of model KnutJaegersberg/Qwen-1_8b-EverythingLM on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T05:24:42.561432(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of KnutJaegersberg/Qwen-1_8b-EverythingLM\n\n\n\nDataset automatically created during the evaluation run of model KnutJaegersberg/Qwen-1_8b-EverythingLM on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T05:24:42.561432(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of yunconglong/7Bx4_DPO\n\n\n\nDataset automatically created during the evaluation run of model yunconglong/7Bx4_DPO on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T05:35:44.285989(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of yunconglong/7Bx4_DPO\n\n\n\nDataset automatically created during the evaluation run of model yunconglong/7Bx4_DPO on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T05:35:44.285989(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

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[]

[ "# Dataset Card for Evaluation run of qnguyen3/quan-1.8b-base\n\n\n\nDataset automatically created during the evaluation run of model qnguyen3/quan-1.8b-base on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T06:21:30.624094(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of qnguyen3/quan-1.8b-base\n\n\n\nDataset automatically created during the evaluation run of model qnguyen3/quan-1.8b-base on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T06:21:30.624094(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of luqmanxyz/Maya_Hermes-2.5-Mistral-7B\n\n\n\nDataset automatically created during the evaluation run of model luqmanxyz/Maya_Hermes-2.5-Mistral-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T06:23:44.665870(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of luqmanxyz/Maya_Hermes-2.5-Mistral-7B\n\n\n\nDataset automatically created during the evaluation run of model luqmanxyz/Maya_Hermes-2.5-Mistral-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T06:23:44.665870(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

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[]

[ "# Dataset Card for Evaluation run of ConvexAI/BurningBruce-003\n\n\n\nDataset automatically created during the evaluation run of model ConvexAI/BurningBruce-003 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T06:25:43.434577(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of ConvexAI/BurningBruce-003\n\n\n\nDataset automatically created during the evaluation run of model ConvexAI/BurningBruce-003 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T06:25:43.434577(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of haoranxu/ALMA-13B-R\n\n\n\nDataset automatically created during the evaluation run of model haoranxu/ALMA-13B-R on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T07:24:09.655926(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of haoranxu/ALMA-13B-R\n\n\n\nDataset automatically created during the evaluation run of model haoranxu/ALMA-13B-R on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T07:24:09.655926(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of BlueNipples/SnowLotus-v2-10.7B\n\n\n\nDataset automatically created during the evaluation run of model BlueNipples/SnowLotus-v2-10.7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T07:51:08.326530(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of BlueNipples/SnowLotus-v2-10.7B\n\n\n\nDataset automatically created during the evaluation run of model BlueNipples/SnowLotus-v2-10.7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T07:51:08.326530(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of yunconglong/7Bx4_DPO_2e\n\n\n\nDataset automatically created during the evaluation run of model yunconglong/7Bx4_DPO_2e on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T07:53:49.728301(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of yunconglong/7Bx4_DPO_2e\n\n\n\nDataset automatically created during the evaluation run of model yunconglong/7Bx4_DPO_2e on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T07:53:49.728301(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "license:apache-2.0", "region:us" ]

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[ "TAGS\n#license-apache-2.0 #region-us \n" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of adamo1139/Yi-34B-200K-AEZAKMI-RAW-1701\n\n\n\nDataset automatically created during the evaluation run of model adamo1139/Yi-34B-200K-AEZAKMI-RAW-1701 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T08:16:53.132202(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of adamo1139/Yi-34B-200K-AEZAKMI-RAW-1701\n\n\n\nDataset automatically created during the evaluation run of model adamo1139/Yi-34B-200K-AEZAKMI-RAW-1701 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T08:16:53.132202(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

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[ "### GSM8K-Zero\nThis dataset is constructed from GSM8K to test the over-reasoning and redundant calculation in the responses of LLMs.\nFor more details, please refer to our github repo or our EACL'24 paper." ]

[ "TAGS\n#region-us \n", "### GSM8K-Zero\nThis dataset is constructed from GSM8K to test the over-reasoning and redundant calculation in the responses of LLMs.\nFor more details, please refer to our github repo or our EACL'24 paper." ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of AA051610/Q\n\n\n\nDataset automatically created during the evaluation run of model AA051610/Q on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T09:11:03.066548(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of AA051610/Q\n\n\n\nDataset automatically created during the evaluation run of model AA051610/Q on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T09:11:03.066548(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "size_categories:n>1T", "3D Vision", "NeRF", "3D Gaussian", "Dataset", "Novel View Synthesis", "Text to 3D", "Image to 3D", "region:us" ]

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[ "# DL3DV-Dataset \nThis repo has all the raw 4K videos of DL3DV-Dataset. We are working hard to review all the dataset to avoid sensitive information. Thank you for your patience.", "# News \n- [x] DL3DV-1K\n- [ ] DL3DV-2K\n- [ ] DL3DV-3K\n- [ ] DL3DV-4K\n- [ ] DL3DV-5K\n- [ ] DL3DV-6K\n- [ ] DL3DV-7K\n- [ ] DL3DV-8K\n- [ ] DL3DV-9K\n- [ ] DL3DV-10K" ]

[ "TAGS\n#size_categories-n>1T #3D Vision #NeRF #3D Gaussian #Dataset #Novel View Synthesis #Text to 3D #Image to 3D #region-us \n", "# DL3DV-Dataset \nThis repo has all the raw 4K videos of DL3DV-Dataset. We are working hard to review all the dataset to avoid sensitive information. Thank you for your patience.", "# News \n- [x] DL3DV-1K\n- [ ] DL3DV-2K\n- [ ] DL3DV-3K\n- [ ] DL3DV-4K\n- [ ] DL3DV-5K\n- [ ] DL3DV-6K\n- [ ] DL3DV-7K\n- [ ] DL3DV-8K\n- [ ] DL3DV-9K\n- [ ] DL3DV-10K" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of alnrg2arg/blockchainlabs_7B_merged_test2_4\n\n\n\nDataset automatically created during the evaluation run of model alnrg2arg/blockchainlabs_7B_merged_test2_4 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T09:52:41.122319(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of alnrg2arg/blockchainlabs_7B_merged_test2_4\n\n\n\nDataset automatically created during the evaluation run of model alnrg2arg/blockchainlabs_7B_merged_test2_4 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T09:52:41.122319(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

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[]

[ "# Dataset Card for Evaluation run of PetroGPT/Voldemort-10B-DPO\n\n\n\nDataset automatically created during the evaluation run of model PetroGPT/Voldemort-10B-DPO on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T12:02:57.927448(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of PetroGPT/Voldemort-10B-DPO\n\n\n\nDataset automatically created during the evaluation run of model PetroGPT/Voldemort-10B-DPO on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T12:02:57.927448(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"protogen-data\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"protogen-data\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"dr_data\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"dr_data\"\n\nMore Information needed" ]

[ "license:cc-by-nc-nd-4.0", "region:us" ]

[]

[]

[ "# discography_v2_cdn\n\nArchive of rebuilt music database\n\nUsing UUID version 7 (uuidv7)" ]

[ "TAGS\n#license-cc-by-nc-nd-4.0 #region-us \n", "# discography_v2_cdn\n\nArchive of rebuilt music database\n\nUsing UUID version 7 (uuidv7)" ]

[ "size_categories:1K<n<10K", "language:en", "arxiv:2402.07844", "region:us" ]

[ "2402.07844" ]

[ "en" ]

[ "# Welcome to Mercury !", "## It is a code efficiency benchmark.", "## Please consider citing our paper: URL" ]

[ "TAGS\n#size_categories-1K<n<10K #language-English #arxiv-2402.07844 #region-us \n", "# Welcome to Mercury !", "## It is a code efficiency benchmark.", "## Please consider citing our paper: URL" ]

[ "task_categories:text-generation", "size_categories:1K<n<10K", "language:ar", "license:cc-by-nc-4.0", "Instruction", "arxiv:2402.03177", "region:us" ]

[ "2402.03177" ]

[ "ar" ]

[]

[ "TAGS\n#task_categories-text-generation #size_categories-1K<n<10K #language-Arabic #license-cc-by-nc-4.0 #Instruction #arxiv-2402.03177 #region-us \n" ]

[ "license:cc0-1.0", "region:us" ]

[]

[]

[]

[ "TAGS\n#license-cc0-1.0 #region-us \n" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of 222gate/bleagle-7b-v0.1-test\n\n\n\nDataset automatically created during the evaluation run of model 222gate/bleagle-7b-v0.1-test on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T12:06:12.141667(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of 222gate/bleagle-7b-v0.1-test\n\n\n\nDataset automatically created during the evaluation run of model 222gate/bleagle-7b-v0.1-test on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T12:06:12.141667(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of alnrg2arg/blockchainlabs_7B_merged_test2_4_prune\n\n\n\nDataset automatically created during the evaluation run of model alnrg2arg/blockchainlabs_7B_merged_test2_4_prune on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T12:08:51.547790(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of alnrg2arg/blockchainlabs_7B_merged_test2_4_prune\n\n\n\nDataset automatically created during the evaluation run of model alnrg2arg/blockchainlabs_7B_merged_test2_4_prune on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T12:08:51.547790(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:text-generation", "size_categories:100K<n<1M", "language:ru", "language:en", "license:mit", "region:us" ]

[]

[ "ru", "en" ]

[]

[ "TAGS\n#task_categories-text-generation #size_categories-100K<n<1M #language-Russian #language-English #license-mit #region-us \n" ]

[ "Lilac", "region:us" ]

[]

[]

[ "# lilac/glaive-code-assistant\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:" ]

[ "TAGS\n#Lilac #region-us \n", "# lilac/glaive-code-assistant\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"instruction_data_train_hf\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"instruction_data_train_hf\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"instruction_data_dev_hf\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"instruction_data_dev_hf\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"instruction_data_test_hf\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"instruction_data_test_hf\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"whalley_dataset\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"whalley_dataset\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of yunconglong/7Bx4_DPO_700\n\n\n\nDataset automatically created during the evaluation run of model yunconglong/7Bx4_DPO_700 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T13:27:07.293796(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of yunconglong/7Bx4_DPO_700\n\n\n\nDataset automatically created during the evaluation run of model yunconglong/7Bx4_DPO_700 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T13:27:07.293796(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of yunconglong/10.7Bx2_DPO_200\n\n\n\nDataset automatically created during the evaluation run of model yunconglong/10.7Bx2_DPO_200 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T13:31:45.156743(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of yunconglong/10.7Bx2_DPO_200\n\n\n\nDataset automatically created during the evaluation run of model yunconglong/10.7Bx2_DPO_200 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T13:31:45.156743(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:question-answering", "task_categories:summarization", "size_categories:100K<n<1M", "language:en", "license:mit", "starmpcc/Asclepius-Synthetic-Clinical-Notes", "BAAI/bge-small-en-v1.5", "medical", "arxiv:2309.00237", "region:us" ]

[ "2309.00237" ]

[ "en" ]

[]

[ "TAGS\n#task_categories-question-answering #task_categories-summarization #size_categories-100K<n<1M #language-English #license-mit #starmpcc/Asclepius-Synthetic-Clinical-Notes #BAAI/bge-small-en-v1.5 #medical #arxiv-2309.00237 #region-us \n" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"whalley_dataset_ver1\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"whalley_dataset_ver1\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"MathInstruct-Core-DifficultyAware\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"MathInstruct-Core-DifficultyAware\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"whalley_dataset_ver2\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"whalley_dataset_ver2\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[]

[ "TAGS\n#region-us \n" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"math_23k_double_standalone\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"math_23k_double_standalone\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"math_23k_double_value_init\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"math_23k_double_value_init\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[]

[ "TAGS\n#region-us \n" ]

[ "Lilac", "region:us" ]

[]

[]

[ "# lilac/open-assistant-conversations-2\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:" ]

[ "TAGS\n#Lilac #region-us \n", "# lilac/open-assistant-conversations-2\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"math_23k_train_numeric_double\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"math_23k_train_numeric_double\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of andrijdavid/Macaroni-7b-Tied\n\n\n\nDataset automatically created during the evaluation run of model andrijdavid/Macaroni-7b-Tied on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T15:12:32.316850(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of andrijdavid/Macaroni-7b-Tied\n\n\n\nDataset automatically created during the evaluation run of model andrijdavid/Macaroni-7b-Tied on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T15:12:32.316850(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Code Textbook\n\n200K+ Synthetic Textbook Samples generated with various Open-Source LLMs including Nous Hermes Mixtral 8x7B, OpenHermes-2.5-Mistral, OpenChat and DeepSeek-Coder." ]

[ "TAGS\n#region-us \n", "# Code Textbook\n\n200K+ Synthetic Textbook Samples generated with various Open-Source LLMs including Nous Hermes Mixtral 8x7B, OpenHermes-2.5-Mistral, OpenChat and DeepSeek-Coder." ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of tenyx/TenyxChat-8x7B-v1\n\n\n\nDataset automatically created during the evaluation run of model tenyx/TenyxChat-8x7B-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T15:44:33.051558(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of tenyx/TenyxChat-8x7B-v1\n\n\n\nDataset automatically created during the evaluation run of model tenyx/TenyxChat-8x7B-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T15:44:33.051558(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:text-generation", "task_categories:question-answering", "size_categories:100K<n<1M", "license:cc-by-nc-nd-4.0", "math", "finance", "region:us" ]

[]

[]

[ "# Simple Math: 2+2=4 -1=3 (LoLo: Learning Only Logical Operations)\n\nJust like my teacher gave me homework, i thought maybe we can also add some of these basics on the trainings of our models.\n\nIt was created with very simple code that is in the repo, if you add more complex operations and so.. please share the code :D thank you\n\nCurrent Code Version: URL (A modification over @win10 for progressive and DPO operation)\n!LoLo: Learning Only Logical Operations", "## Does it Works?", "### 34BEAGLES Evaluation:", "### 34BEAGLES-MATH Evaluation\n\n\nBut it gets better, because when increasing length and complexity, the marks are even superior:\n\nOn a 3.20% GSM Improvement compared to its base model.", "## Note to contributors:\nthank you to those contributing on the experiment with beautiful commits and good spirit\n\n* Feel free to contribute on the readme Evaluation tests.\n* Lets aim to build an ablation & paper together. All contributors will be cited.", "## Versions\n\n\ns\nIf you use Simple Math o train your model, please cite on the modelcard or the paper." ]

[ "TAGS\n#task_categories-text-generation #task_categories-question-answering #size_categories-100K<n<1M #license-cc-by-nc-nd-4.0 #math #finance #region-us \n", "# Simple Math: 2+2=4 -1=3 (LoLo: Learning Only Logical Operations)\n\nJust like my teacher gave me homework, i thought maybe we can also add some of these basics on the trainings of our models.\n\nIt was created with very simple code that is in the repo, if you add more complex operations and so.. please share the code :D thank you\n\nCurrent Code Version: URL (A modification over @win10 for progressive and DPO operation)\n!LoLo: Learning Only Logical Operations", "## Does it Works?", "### 34BEAGLES Evaluation:", "### 34BEAGLES-MATH Evaluation\n\n\nBut it gets better, because when increasing length and complexity, the marks are even superior:\n\nOn a 3.20% GSM Improvement compared to its base model.", "## Note to contributors:\nthank you to those contributing on the experiment with beautiful commits and good spirit\n\n* Feel free to contribute on the readme Evaluation tests.\n* Lets aim to build an ablation & paper together. All contributors will be cited.", "## Versions\n\n\ns\nIf you use Simple Math o train your model, please cite on the modelcard or the paper." ]

[ "region:us" ]

[]

[]

[ "# Small RedPajama-v2\n500K Samples from RedPajama-v2" ]

[ "TAGS\n#region-us \n", "# Small RedPajama-v2\n500K Samples from RedPajama-v2" ]

[ "size_categories:100K<n<1M", "language:en", "license:cc-by-4.0", "region:us" ]

[]

[ "en" ]

[ "## Worded Math\n\n- Version 1.1\n- Updated for general improvements\n\n1 Million examples of word-based math (in English) with number results.\n\nCreated from fglbit/simple-math.\n\nUsing this python code (requires 'inflect'):" ]

[ "TAGS\n#size_categories-100K<n<1M #language-English #license-cc-by-4.0 #region-us \n", "## Worded Math\n\n- Version 1.1\n- Updated for general improvements\n\n1 Million examples of word-based math (in English) with number results.\n\nCreated from fglbit/simple-math.\n\nUsing this python code (requires 'inflect'):" ]

[ "region:us" ]

[]

[]

[ "# Extra Small RedPajama-v2\n250K Samples from RedPajama-v2" ]

[ "TAGS\n#region-us \n", "# Extra Small RedPajama-v2\n250K Samples from RedPajama-v2" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:text-to-image", "size_categories:1K<n<10K", "language:en", "license:apache-2.0", "sample", "example", "comparison", "stable-diffusion", "stable-diffusion-xl", "animagine", "region:us" ]

[]

[ "en" ]

[]

[ "TAGS\n#task_categories-text-to-image #size_categories-1K<n<10K #language-English #license-apache-2.0 #sample #example #comparison #stable-diffusion #stable-diffusion-xl #animagine #region-us \n" ]

[ "region:us" ]

[]

[]

[ "# The Stack smol-XL\nA cleaned version of The Stack smol-XL" ]

[ "TAGS\n#region-us \n", "# The Stack smol-XL\nA cleaned version of The Stack smol-XL" ]

[ "task_categories:text-classification", "size_categories:1K<n<10K", "language:nl", "license:gpl", "medical", "synthetic", "region:us" ]

[]

[ "nl" ]

[ "### Data Collection\n\n- Data type: Text (synthetic notes)\n- Source: Generated by OpenAI API\n- Language: Dutch\n- Period: January 2024\n- Method: Generated by OpenAI's language model 'gpt-3.5-turbo'", "### Dataset Characteristics\n\n- Size: 8,699 rows (train: 16 clients, 5788 notes, valid: 4 clients, 1455 notes, test: 4 clients, 1456 notes)\n- Format: csv\n- Fields:\n - ct_id: Client ID\n - datum: Date\n - discipline: Role of the author of the note\n - rapportage: Note text\n - onrust: Boolean value set to True if the agitation score exceeds 50\n - onrustscore: Level of agitation described in the nursing care note.", "## Intended Use\n\n- Primary Use: Fine-tuning LLMs for applications in healthcare, focusing on nursing homes.\n- Use Cases: Predicting agitation scores.", "## Ethical Considerations\n\n- Bias: The dataset, generated by AI, may exhibit language and contextual biases, potentially influencing model predictions and affecting their fairness and accuracy", "## Versioning\n\n- Version: 1.0\n- Date: 20-01-2024" ]

[ "TAGS\n#task_categories-text-classification #size_categories-1K<n<10K #language-Dutch #license-gpl #medical #synthetic #region-us \n", "### Data Collection\n\n- Data type: Text (synthetic notes)\n- Source: Generated by OpenAI API\n- Language: Dutch\n- Period: January 2024\n- Method: Generated by OpenAI's language model 'gpt-3.5-turbo'", "### Dataset Characteristics\n\n- Size: 8,699 rows (train: 16 clients, 5788 notes, valid: 4 clients, 1455 notes, test: 4 clients, 1456 notes)\n- Format: csv\n- Fields:\n - ct_id: Client ID\n - datum: Date\n - discipline: Role of the author of the note\n - rapportage: Note text\n - onrust: Boolean value set to True if the agitation score exceeds 50\n - onrustscore: Level of agitation described in the nursing care note.", "## Intended Use\n\n- Primary Use: Fine-tuning LLMs for applications in healthcare, focusing on nursing homes.\n- Use Cases: Predicting agitation scores.", "## Ethical Considerations\n\n- Bias: The dataset, generated by AI, may exhibit language and contextual biases, potentially influencing model predictions and affecting their fairness and accuracy", "## Versioning\n\n- Version: 1.0\n- Date: 20-01-2024" ]

[ "source_datasets:databricks/databricks-dolly-15k", "license:cc-by-sa-3.0", "region:us" ]

[]

[]

[]

[ "TAGS\n#source_datasets-databricks/databricks-dolly-15k #license-cc-by-sa-3.0 #region-us \n" ]

[ "license:mit", "region:us" ]

[]

[]

[ "# ALFRED Dataset for ABP\nWe provide the ALFRED dataset used for <a href=\"URL target=\"_new\">ABP</a> including ResNet-18 features of egocentric and surrounding views, annotations, etc.\nThe surrdounding views are from four navigable actions defined in ALFRED: RotateLeft (90°), LookUp(15°), LookDown(15°), and RotateRight(90°).\nThe file structure is almost identical to the ALFRED dataset, so refer to <a href=\"URL for more details.", "## Download the dataset\nMove to the root (denoted by ALFRED_ROOT below) of the ABP (or related work) repo and clone this repository by following the commands below.\\\nNote: This dataset is quite large (~1.6T).\n\n\nAfter downloading the dataset, you may directly load a surrounding feature and the expected outcome is as below.\n\n\nThe 0-dimension of the feature corresponds to the respective view directions as below.\n<ul>\n <li>0: left view (RotateLeft)</li>\n <li>1: up view (LookUp)</li>\n <li>2: front (egocentric) view (no action)</li>\n <li>3: down view (LookDown)</li>\n <li>4: right view (RotateRight)</li>\n</ul>\n\nInspired by <a href=\"URL we apply image augmentation to the agent's visual observation.\nWe apply two types of image augmentation: 1) swapping color channels of images and 2) AutoAugment.\n- No augmentation: (feat_conv_panoramic.pt)\n- Swapping color channels: (feat_conv_colorSwap1_panoramic.pt, feat_conv_colorSwap2_panoramic.pt)\n- AutoAugment: (feat_conv_onlyAutoAug1_panoramic.pt ~ feat_conv_onlyAutoAug4_panoramic.pt)", "## Related work that uses this dataset\n<ul>\n <li>\n <a href=\"URL\n Online Continual Learning for Interactive Instruction Following Agents\n </a>\n <br>\n <a href=\"URL target=\"_new\">\n Byeonghwi Kim\n </a>^*,\n <a href=\"\" target=\"_new\">\n Minhyuk Seo\n </a>^*,\n <a href=\"URL target=\"_new\">\n Jonghyun Choi\n </a>\n <br>\n ICLR 2024\n </li>\n\n <li>\n <a href=\"URL target=\"_new\">\n Multi-Level Compositional Reasoning for Interactive Instruction Following\n </a>\n <br>\n <a href=\"URL target=\"_new\">\n Suvaansh Bhambri\n </a>^*,\n <a href=\"URL target=\"_new\">\n Byeonghwi Kim\n </a>^*,\n <a href=\"URL target=\"_new\">\n Jonghyun Choi\n </a>\n <br>\n AAAI 2023 (Oral)\n </li>\n \n <li>\n <a href=\"URL target=\"_new\">\n Factorizing Perception and Policy for Interactive Instruction Following\n </a>\n <br>\n <a href=\"URL target=\"_new\">\n Kunal Pratap Singh\n </a>^*,\n <a href=\"URL target=\"_new\">\n Suvaansh Bhambri\n </a>^*,\n <a href=\"URL target=\"_new\">\n Byeonghwi Kim\n </a>^*,\n <a href=\"URL target=\"_new\">\n Roozbeh Mottaghi\n </a>,\n <a href=\"URL target=\"_new\">\n Jonghyun Choi\n </a>.\n <br>\n ICCV 2021\n </li>\n \n <li>\n <a href=\"URL target=\"_new\">\n Agent with the Big Picture: Perceiving Surroundings for Interactive Instruction Following\n </a>\n <br>\n <a href=\"URL target=\"_new\">\n Byeonghwi Kim\n </a>,\n <a href=\"URL target=\"_new\">\n Suvaansh Bhambri\n </a>,\n <a href=\"URL target=\"_new\">\n Kunal Pratap Singh\n </a>,\n <a href=\"URL target=\"_new\">\n Roozbeh Mottaghi\n </a>,\n <a href=\"URL target=\"_new\">\n Jonghyun Choi\n </a>.\n <br>\n Embodied AI Workshop @ CVPR 2021\n </li>\n</ul>\n\nIf you find this repository useful, please cite this repository." ]

[ "TAGS\n#license-mit #region-us \n", "# ALFRED Dataset for ABP\nWe provide the ALFRED dataset used for <a href=\"URL target=\"_new\">ABP</a> including ResNet-18 features of egocentric and surrounding views, annotations, etc.\nThe surrdounding views are from four navigable actions defined in ALFRED: RotateLeft (90°), LookUp(15°), LookDown(15°), and RotateRight(90°).\nThe file structure is almost identical to the ALFRED dataset, so refer to <a href=\"URL for more details.", "## Download the dataset\nMove to the root (denoted by ALFRED_ROOT below) of the ABP (or related work) repo and clone this repository by following the commands below.\\\nNote: This dataset is quite large (~1.6T).\n\n\nAfter downloading the dataset, you may directly load a surrounding feature and the expected outcome is as below.\n\n\nThe 0-dimension of the feature corresponds to the respective view directions as below.\n<ul>\n <li>0: left view (RotateLeft)</li>\n <li>1: up view (LookUp)</li>\n <li>2: front (egocentric) view (no action)</li>\n <li>3: down view (LookDown)</li>\n <li>4: right view (RotateRight)</li>\n</ul>\n\nInspired by <a href=\"URL we apply image augmentation to the agent's visual observation.\nWe apply two types of image augmentation: 1) swapping color channels of images and 2) AutoAugment.\n- No augmentation: (feat_conv_panoramic.pt)\n- Swapping color channels: (feat_conv_colorSwap1_panoramic.pt, feat_conv_colorSwap2_panoramic.pt)\n- AutoAugment: (feat_conv_onlyAutoAug1_panoramic.pt ~ feat_conv_onlyAutoAug4_panoramic.pt)", "## Related work that uses this dataset\n<ul>\n <li>\n <a href=\"URL\n Online Continual Learning for Interactive Instruction Following Agents\n </a>\n <br>\n <a href=\"URL target=\"_new\">\n Byeonghwi Kim\n </a>^*,\n <a href=\"\" target=\"_new\">\n Minhyuk Seo\n </a>^*,\n <a href=\"URL target=\"_new\">\n Jonghyun Choi\n </a>\n <br>\n ICLR 2024\n </li>\n\n <li>\n <a href=\"URL target=\"_new\">\n Multi-Level Compositional Reasoning for Interactive Instruction Following\n </a>\n <br>\n <a href=\"URL target=\"_new\">\n Suvaansh Bhambri\n </a>^*,\n <a href=\"URL target=\"_new\">\n Byeonghwi Kim\n </a>^*,\n <a href=\"URL target=\"_new\">\n Jonghyun Choi\n </a>\n <br>\n AAAI 2023 (Oral)\n </li>\n \n <li>\n <a href=\"URL target=\"_new\">\n Factorizing Perception and Policy for Interactive Instruction Following\n </a>\n <br>\n <a href=\"URL target=\"_new\">\n Kunal Pratap Singh\n </a>^*,\n <a href=\"URL target=\"_new\">\n Suvaansh Bhambri\n </a>^*,\n <a href=\"URL target=\"_new\">\n Byeonghwi Kim\n </a>^*,\n <a href=\"URL target=\"_new\">\n Roozbeh Mottaghi\n </a>,\n <a href=\"URL target=\"_new\">\n Jonghyun Choi\n </a>.\n <br>\n ICCV 2021\n </li>\n \n <li>\n <a href=\"URL target=\"_new\">\n Agent with the Big Picture: Perceiving Surroundings for Interactive Instruction Following\n </a>\n <br>\n <a href=\"URL target=\"_new\">\n Byeonghwi Kim\n </a>,\n <a href=\"URL target=\"_new\">\n Suvaansh Bhambri\n </a>,\n <a href=\"URL target=\"_new\">\n Kunal Pratap Singh\n </a>,\n <a href=\"URL target=\"_new\">\n Roozbeh Mottaghi\n </a>,\n <a href=\"URL target=\"_new\">\n Jonghyun Choi\n </a>.\n <br>\n Embodied AI Workshop @ CVPR 2021\n </li>\n</ul>\n\nIf you find this repository useful, please cite this repository." ]

[ "region:us" ]

[]

[]

[ "# RefinedWeb 1M Medium\nCurated RefinedWeb with medium context length (2048 <= ctx_len <= 8192)" ]

[ "TAGS\n#region-us \n", "# RefinedWeb 1M Medium\nCurated RefinedWeb with medium context length (2048 <= ctx_len <= 8192)" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of ConvexAI/Metabird-7B\n\n\n\nDataset automatically created during the evaluation run of model ConvexAI/Metabird-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T17:15:55.821392(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of ConvexAI/Metabird-7B\n\n\n\nDataset automatically created during the evaluation run of model ConvexAI/Metabird-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T17:15:55.821392(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "license:apache-2.0", "synthetic", "region:us" ]

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[ "TAGS\n#license-apache-2.0 #synthetic #region-us \n" ]

[ "license:apache-2.0", "synthetic", "region:us" ]

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[ "TAGS\n#license-apache-2.0 #synthetic #region-us \n" ]

[ "region:us" ]

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[]

[ "# Dataset Card for \"noisy_vctk_16k_extract_unit\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"noisy_vctk_16k_extract_unit\"\n\nMore Information needed" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of freecs/Zero-7B-test-2\n\n\n\nDataset automatically created during the evaluation run of model freecs/Zero-7B-test-2 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T18:46:57.239901(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of freecs/Zero-7B-test-2\n\n\n\nDataset automatically created during the evaluation run of model freecs/Zero-7B-test-2 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T18:46:57.239901(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

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[ "# Dataset Card for \"Quant-Trading-Instruct\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"Quant-Trading-Instruct\"\n\nMore Information needed" ]

[ "task_categories:image-to-text", "task_categories:image-to-image", "task_categories:text-to-image", "size_categories:1K<n<10K", "language:en", "license:cc0-1.0", "cc0", "public domain", "copyright-free", "stock photos", "images", "region:us" ]

[]

[ "en" ]

[ "# CC0 Stock Images Dataset\n\nThis dataset contains a collection of stock images that are covered by the Creative Commons Zero (CC0) License, meaning they are free for personal and commercial use with no attribution required. It is designed to support a variety of computer vision tasks such as image tagging, categorization, and machine learning model training.", "## Disclaimer\nWhile every effort has been made to ensure the reliability and correctness of the data presented, the dataset is provided \"as is\" without any guarantee. If you find any issues, please report them to the dataset maintainers.", "## Dataset Structure\n\nThe dataset includes the following features:\n\n- 'image': The raw bytes of the image, which can be read using image processing libraries like PIL or OpenCV.\n- 'tags': A string containing comma-separated tags related to the content of the image.", "## Size of the Dataset\n\nThe size of the dataset is _1000_ images. (To be updated with more soon)", "## Use Cases\n\nThis dataset can be used for a variety of purposes, including but not limited to:\n\n- Training and evaluating image classification models.\n- Developing and testing image tagging algorithms.\n- Visual data analysis and machine learning research.\n- Creating artwork and design projects.", "## License\n\nAll images in this dataset are available under the CC0 License. You can copy, modify, distribute, and perform the work, even for commercial purposes, all without asking permission.", "## Acknowledgements\n\nThis dataset has been compiled from various sources that provide free stock images under the CC0 License. We extend our gratitude to the photographers and creators who have contributed their work to the public domain.", "## Accessing the Dataset\n\nThis dataset is hosted on the Hugging Face Hub. You can access and download the dataset using the Hugging Face 'datasets' library with the following command:", "## Contributing\nWe welcome contributions to this dataset, whether it's adding more images, improving the tags, or any other improvements you can offer. Please follow the standard procedures for contributing to datasets on the Hugging Face Hub." ]

[ "TAGS\n#task_categories-image-to-text #task_categories-image-to-image #task_categories-text-to-image #size_categories-1K<n<10K #language-English #license-cc0-1.0 #cc0 #public domain #copyright-free #stock photos #images #region-us \n", "# CC0 Stock Images Dataset\n\nThis dataset contains a collection of stock images that are covered by the Creative Commons Zero (CC0) License, meaning they are free for personal and commercial use with no attribution required. It is designed to support a variety of computer vision tasks such as image tagging, categorization, and machine learning model training.", "## Disclaimer\nWhile every effort has been made to ensure the reliability and correctness of the data presented, the dataset is provided \"as is\" without any guarantee. If you find any issues, please report them to the dataset maintainers.", "## Dataset Structure\n\nThe dataset includes the following features:\n\n- 'image': The raw bytes of the image, which can be read using image processing libraries like PIL or OpenCV.\n- 'tags': A string containing comma-separated tags related to the content of the image.", "## Size of the Dataset\n\nThe size of the dataset is _1000_ images. (To be updated with more soon)", "## Use Cases\n\nThis dataset can be used for a variety of purposes, including but not limited to:\n\n- Training and evaluating image classification models.\n- Developing and testing image tagging algorithms.\n- Visual data analysis and machine learning research.\n- Creating artwork and design projects.", "## License\n\nAll images in this dataset are available under the CC0 License. You can copy, modify, distribute, and perform the work, even for commercial purposes, all without asking permission.", "## Acknowledgements\n\nThis dataset has been compiled from various sources that provide free stock images under the CC0 License. We extend our gratitude to the photographers and creators who have contributed their work to the public domain.", "## Accessing the Dataset\n\nThis dataset is hosted on the Hugging Face Hub. You can access and download the dataset using the Hugging Face 'datasets' library with the following command:", "## Contributing\nWe welcome contributions to this dataset, whether it's adding more images, improving the tags, or any other improvements you can offer. Please follow the standard procedures for contributing to datasets on the Hugging Face Hub." ]

[ "region:us" ]

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[ "# Dataset Card for \"noisy_vctk_16k_synth\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"noisy_vctk_16k_synth\"\n\nMore Information needed" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of Danielbrdz/Barcenas-Tiny-1.1b-DPO\n\n\n\nDataset automatically created during the evaluation run of model Danielbrdz/Barcenas-Tiny-1.1b-DPO on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T20:17:56.012496(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of Danielbrdz/Barcenas-Tiny-1.1b-DPO\n\n\n\nDataset automatically created during the evaluation run of model Danielbrdz/Barcenas-Tiny-1.1b-DPO on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-20T20:17:56.012496(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "source_datasets:Amod/mental_health_counseling_conversations", "license:openrail", "region:us" ]

[]

[]

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[ "TAGS\n#source_datasets-Amod/mental_health_counseling_conversations #license-openrail #region-us \n" ]