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title: InternVL2.5 Image Analyzer | |
emoji: 🖼️ | |
colorFrom: blue | |
colorTo: purple | |
sdk: gradio | |
sdk_version: 3.50.0 | |
app_file: app.py | |
pinned: false | |
# InternVL2.5 Image Analyzer | |
This Hugging Face Space demonstrates the capabilities of the [InternVL2.5 model](https://huggingface.co/OpenGVLab/InternVL2_5-8B), a powerful multimodal model that can analyze images and respond to questions about them. | |
## Features | |
- Upload your own images for analysis | |
- Choose from predefined prompts or create your own | |
- Detailed image understanding and description | |
- Text recognition in images | |
- Visual reasoning capabilities | |
## Model Details | |
This space uses the InternVL2.5-8B model, which is a multimodal large language model (MLLM) with approximately 8.1 billion parameters. The model was developed by OpenGVLab and demonstrates strong capabilities in various visual understanding tasks. | |
### Architecture | |
InternVL2.5 combines a vision encoder (based on the InternViT architecture) with a language model, allowing it to process both visual and textual information. | |
## Example Prompts | |
Here are some prompts you can try: | |
1. Describe this image in detail. | |
2. What can you tell me about this image? | |
3. Is there any text in this image? If so, can you read it? | |
4. What is the main subject of this image? | |
5. What emotions or feelings does this image convey? | |
6. Describe the composition and visual elements of this image. | |
7. Summarize what you see in this image in one paragraph. | |
## Usage | |
1. Upload an image using the file uploader | |
2. Select a prompt from the dropdown or write your own | |
3. Click "Submit" to get the analysis | |
## Credits | |
This application uses the InternVL2.5 model by OpenGVLab. For more information about the model, check out: | |
- [OpenGVLab/InternVL Repository](https://github.com/OpenGVLab/InternVL) | |
- [InternVL Documentation](https://internvl.readthedocs.io/en/latest/) | |
## License | |
The InternVL2.5 model is licensed under the MIT License. |