Duplicate from StampyAI/alignment-research-dataset

Co-authored-by: Cheng2 <[email protected]>

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
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+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
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+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
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+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
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+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
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+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+language:
+- en
+license: mit
+size_categories:
+- 10K<n<100K
+task_categories:
+- question-answering
+pretty_name: alignment-research-dataset
+dataset_info:
+  features:
+  - name: id
+    dtype: string
+  - name: source
+    dtype: string
+  - name: title
+    dtype: string
+  - name: text
+    dtype: large_string
+  - name: url
+    dtype: string
+  - name: date_published
+    dtype: string
+  - name: authors
+    sequence: string
+  - name: summary
+    sequence: string
+  - name: source_type
+    dtype: string
+  - name: book_title
+    dtype: string
+  - name: karma
+    dtype: int32
+  - name: votes
+    dtype: int32
+  - name: words
+    dtype: int32
+  - name: comment_count
+    dtype: int32
+  - name: tags
+    sequence: string
+  - name: modified_at
+    dtype: string
+  - name: alias
+    dtype: string
+  - name: data_last_modified
+    dtype: string
+  - name: abstract
+    dtype: string
+  - name: author_comment
+    dtype: string
+  - name: journal_ref
+    dtype: string
+  - name: doi
+    dtype: string
+  - name: primary_category
+    dtype: string
+  - name: categories
+    sequence: string
+  - name: initial_source
+    dtype: string
+  - name: bibliography_bib
+    sequence:
+    - name: title
+      dtype: string
+  config_name: all
+  splits:
+  - name: train
+    num_bytes: 471644446
+    num_examples: 14271
+  download_size: 484827959
+  dataset_size: 471644446
+---
+# AI Alignment Research Dataset
+
+The AI Alignment Research Dataset is a collection of documents related to AI Alignment and Safety from various books, research papers, and alignment related blog posts. This is a work in progress. Components are still undergoing a cleaning process to be updated more regularly.
+
+## Sources
+
+Here are the list of sources along with sample contents:
+
+- [agentmodel](https://agentmodels.org/)
+- [agisf](https://course.aisafetyfundamentals.com/) - recommended readings from AGI Safety Fundamentals
+- [aisafety.info](https://aisafety.info/) - Stampy's FAQ
+- [alignmentforum](https://www.alignmentforum.org)
+- [alignment_newsletter](https://rohinshah.com/alignment-newsletter/)
+- [arbital](https://arbital.com/)
+- [arxiv](https://arxiv.org/) - relevant research papers
+
+- blogs - entire websites automatically scraped
+  - [AI Impacts](https://aiimpacts.org/)
+  - [AI Safety Camp](https://aisafety.camp/)
+  - [carado.moe](https://carado.moe/)
+  - [Cold Takes](https://www.cold-takes.com/)
+  - [DeepMind technical blogs](https://www.deepmind.com/blog-categories/technical-blogs)
+  - [DeepMind AI Safety Research](https://deepmindsafetyresearch.medium.com/)
+  - [EleutherAI](https://blog.eleuther.ai/)
+  - [generative.ink](https://generative.ink/posts/)
+  - [Gwern Branwen's blog](https://gwern.net/)
+  - [Jack Clark's Import AI](https://importai.substack.com/)
+  - [MIRI](https://intelligence.org/)
+  - [Jacob Steinhardt's blog](https://jsteinhardt.wordpress.com/)
+  - [ML Safety Newsletter](https://newsletter.mlsafety.org/)
+  - [Transformer Circuits Thread](https://transformer-circuits.pub/)
+  - [Open AI Research](https://openai.com/research/)
+  - [Victoria Krakovna's blog](https://vkrakovna.wordpress.com/)
+  - [Eliezer Yudkowsky's blog](https://www.yudkowsky.net/)
+
+- [distill](https://distill.pub/)
+- [eaforum](https://forum.effectivealtruism.org/) - selected posts
+- [lesswrong](https://www.lesswrong.com/) - selected posts
+
+- special_docs - individual documents curated from various resources
+  - [Make a suggestion](https://bit.ly/ard-suggestion) for sources not already in the dataset
+
+- youtube - playlists & channels
+  - [AI Alignment playlist](https://www.youtube.com/playlist?list=PLCRVRLd2RhZTpdUdEzJjo3qhmX3y3skWA) and other lists
+  - [AI Explained](https://www.youtube.com/@aiexplained-official)
+  - [Evan Hubinger's AI Safety Talks](https://www.youtube.com/@aisafetytalks)
+  - [AI Safety Reading Group](https://www.youtube.com/@aisafetyreadinggroup/videos)
+  - [AiTech - TU Delft](https://www.youtube.com/@AiTechTUDelft/)
+  - [Rob Miles AI](https://www.youtube.com/@RobertMilesAI)
+
+## Keys
+
+All entries contain the following keys:
+
+- `id` - string of unique identifier
+- `source` - string of data source listed above
+- `title` - string of document title of document
+- `authors` - list of strings
+- `text` - full text of document content
+- `url` - string of valid link to text content
+- `date_published` - in UTC format
+
+Additional keys may be available depending on the source document.
+
+## Usage
+
+Execute the following code to download and parse the files:
+
+```python
+from datasets import load_dataset
+data = load_dataset('StampyAI/alignment-research-dataset')
+```
+
+To only get the data for a specific source, pass it in as the second argument, e.g.:
+
+```python
+from datasets import load_dataset
+data = load_dataset('StampyAI/alignment-research-dataset', 'lesswrong')
+```
+
+## Limitations and Bias
+
+LessWrong posts have overweighted content on doom and existential risk, so please beware in training or finetuning generative language models on the dataset.
+
+## Contributing
+
+The scraper to generate this dataset is open-sourced on [GitHub](https://github.com/StampyAI/alignment-research-dataset) and currently maintained by volunteers at StampyAI / AI Safety Info. [Learn more](https://coda.io/d/AI-Safety-Info_dfau7sl2hmG/Get-involved_susRF#_lufSr) or join us on [Discord](https://discord.gg/vjFSCDyMCy).
+
+## Rebuilding info
+
+This README contains info about the number of rows and their features which should be rebuilt each time datasets get changed. To do so, run:
+
+    datasets-cli test ./alignment-research-dataset --save_info --all_configs
+
+## Citing the Dataset
+
+For more information, here is the [paper](https://arxiv.org/abs/2206.02841) and [LessWrong](https://www.lesswrong.com/posts/FgjcHiWvADgsocE34/a-descriptive-not-prescriptive-overview-of-current-ai) post. Please use the following citation when using the dataset:
+
+Kirchner, J. H., Smith, L., Thibodeau, J., McDonnell, K., and Reynolds, L. "Understanding AI alignment research: A Systematic Analysis." arXiv preprint arXiv:2022.4338861 (2022).

agisf.jsonl

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+oid sha256:87339fe27558475ed2419d0d92af20b5035a686821b82440c1cecefe2a21fdf3
+size 3168051

alignment-research-dataset.py

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+import json
+from pathlib import Path
+
+import datasets
+from datasets import Value, Sequence, Features
+
+
+_CITATION = '''
+@article{kirchner2022understanding,
+  title={Understanding AI Alignment Research: A Systematic Analysis},
+  author={Kirchner, Jan H and Smith, Logan and Thibodeau, Jacques and McDonnell, Kyle and Reynolds, Laria},
+  journal={arXiv preprint arXiv:2022.4338861},
+  year={2022}
+}
+'''
+
+_DESCRIPTION = """The AI Alignment Research Dataset is a collection of documents related to AI Alignment and Safety from various books, research papers, and alignment related blog posts."""
+
+_HOMEPAGE = "https://github.com/StampyAI/alignment-research-dataset"
+
+_LICENSE = "MIT license"
+
+_VERSION_ = '0.0.0'
+
+
+def iterate_file(filename):
+    print(filename)
+    with open(filename) as f:
+        for l in f:
+            try:
+                yield json.loads(l)
+            except Exception as e:
+                print(f'Could not parse: {l}')
+
+
+## Feature extractor helpers
+def get_type(value):
+    """Recursively get the huggingface type for the provided value."""
+    if value is None:
+        return None
+    if value and isinstance(value, (tuple, list)):
+        return features.Sequence(
+            get_type(value[0])
+        )
+    if value and isinstance(value, dict):
+        return {k: get_type(v) for k, v in value.items()}
+    if isinstance(value, str):
+        return Value('string')
+    if isinstance(value, int):
+        return Value('int32')
+    if isinstance(value, float):
+        return Value('double')
+    if isinstance(value, bool):
+        return Value('bool')
+    return None
+
+
+def print_extra_features(files):
+    """Go through all the provided files, and get the non default features for the given file.
+
+    This can be done manually but would be a hassle.
+    It's assumed that the files contain a json object on each line.
+    """
+    ignored_keys = [
+        'comments',  # Comments are arbitrarily nested objects, which doesn't play nice with huggingface
+    ]
+
+    per_file = {}
+    for filename in sorted(files):
+        extra_types = {}
+        for item in iterate_file(filename):
+            for k, v in item.items():
+                if (k not in extra_types or not extra_types[k]) and k not in ignored_keys and k not in DEFAULT_FEATURES:
+                    extra_types[k] = get_type(v)
+        per_file[filename] = extra_types
+
+    print('DATASOURCES = {')
+    for k, features in per_file.items():
+        vals = ',\n'.join(f"        '{k}': {v}" for k, v in features.items())
+        print(f"    '{k.stem}': #\n{vals}\n    $,".replace('#', '{').replace('$', '}'))
+    print('}')
+
+
+# These keys are present in all files
+DEFAULT_FEATURES = {
+    'id': Value('string'),
+    'source': Value('string'),
+    'title': Value('string'),
+    'text': Value('large_string'),
+    'url': Value('string'),
+    'date_published': Value(dtype='string'),
+    'authors': Sequence(feature=Value(dtype='string'), length=-1),
+    'summary': Sequence(feature=Value(dtype='string'), length=-1),
+    'source_type': Value(dtype='string'),
+}
+
+
+# Per datasource additional features
+DATASOURCES = {
+    'agentmodels': {
+        'book_title': Value(dtype='string'),
+    },
+    'agisf': {},
+    'aisafety.info': {},
+    'alignmentforum': {
+        'karma': Value(dtype='int32'),
+        'votes': Value(dtype='int32'),
+        'words': Value(dtype='int32'),
+        'comment_count': Value(dtype='int32'),
+        'tags': Sequence(feature=Value(dtype='string')),
+        'modified_at': Value(dtype='string'),
+    },
+    'arbital': {
+        'alias': Value(dtype='string'),
+        'tags': Sequence(feature=Value(dtype='string')),
+    },
+    'arxiv': {
+        'data_last_modified': Value(dtype='string'),
+        'abstract': Value(dtype='string'),
+        'author_comment': Value(dtype='string'),
+        'journal_ref': Value(dtype='string'),
+        'doi': Value(dtype='string'),
+        'primary_category': Value(dtype='string'),
+        'categories': Sequence(feature=Value(dtype='string'), length=-1),
+    },
+    'blogs': {
+        'initial_source': Value(dtype='string'),
+    },
+    'distill': {
+        'abstract': Value(dtype='string'),
+        'journal_ref': Value(dtype='string'),
+        'doi': Value(dtype='string'),
+        'bibliography_bib': Sequence(feature={'title': Value(dtype='string')}, length=-1),
+    },
+    'eaforum': {
+        'karma': Value(dtype='int32'),
+        'votes': Value(dtype='int32'),
+        'words': Value(dtype='int32'),
+        'comment_count': Value(dtype='int32'),
+        'tags': Sequence(feature=Value(dtype='string')),
+        'modified_at': Value(dtype='string'),
+    },
+    'lesswrong': {
+        'karma': Value(dtype='int32'),
+        'votes': Value(dtype='int32'),
+        'words': Value(dtype='int32'),
+        'comment_count': Value(dtype='int32'),
+        'tags': Sequence(feature=Value(dtype='string')),
+        'modified_at': Value(dtype='string'),
+    },
+    'special_docs': {},
+    'youtube': {},
+}
+
+
+def join_features(features, to_join):
+    """Recursively join the provided dicts.
+
+    `to_join` can either be a dict to be merged, or a list of dicts to merge.
+    """
+    if not to_join:
+        return Features(features)
+    if isinstance(to_join, dict):
+        return Features(dict(features, **to_join))
+    return join_features(dict(features, **to_join[0]), to_join[1:])
+
+
+class AlignmentResearchDatasetConfig(datasets.BuilderConfig):
+    """BuilderConfig for AlignmentResaerchDataset."""
+
+    def __init__(self, sources, features, **kwargs):
+        """BuilderConfig for AlignmentResaerchDataset.
+
+        :param List[string] sources: the sources which will be used by this config
+        """
+        super().__init__(version=datasets.Version(_VERSION_), **kwargs)
+        self.sources = sources
+        self.features = join_features(DEFAULT_FEATURES, features)
+
+    @property
+    def files(self):
+        return [f'{source}.jsonl' for source in self.sources]
+
+
+class AlignmentResaerchDataset(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version(_VERSION_)
+
+    BUILDER_CONFIGS = [
+        AlignmentResearchDatasetConfig(
+            name='all',
+            description='All data files',
+            sources=list(DATASOURCES.keys()),
+            features=list(DATASOURCES.values())
+        )
+    ] + [
+        AlignmentResearchDatasetConfig(name=source, sources=[source], features=features) for source, features in DATASOURCES.items()
+    ]
+    DEFAULT_CONFIG_NAME = 'all'
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=self.config.features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_files = dl_manager.download_and_extract(self.config.files)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={'files': downloaded_files}
+            )
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, files):
+        seen = set()
+
+        def is_good(item):
+            item_id = item and item.get('id')
+            if not item_id or item_id in seen:
+                return False
+            seen.add(item_id)
+
+            return item['text'] not in [None, '', 'n/a']
+
+        def prepare_example(item):
+            return item['id'], {k: item.get(k) for k in self.config.features}
+
+        lines = (item for filename in files for item in iterate_file(filename))
+        for item in map(prepare_example, filter(is_good, lines)):
+            yield item

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