| --- |
| license: apache-2.0 |
| base_model: |
| - mistralai/Pixtral-12B-2409 |
| library_name: transformers |
| --- |
| # Pixtral-12B Vision Encoder |
|
|
| ## Model Overview |
| This repository provides direct access to the vision encoder module extracted from the Pixtral-12B multimodal model. By isolating the vision encoder, we enable researchers and developers to leverage the powerful visual feature extraction capabilities for downstream vision tasks. |
|
|
| ## Key Features |
| - **Standalone Vision Encoder**: Extracted from the full Pixtral-12B model |
| - **Lightweight Architecture**: Optimized 400M parameter vision encoder |
| - **Flexible Usage**: Easily integrated into various computer vision pipelines |
| - **No Unnecessary Decoder Weights**: Trimmed for efficient vision-specific applications |
|
|
| ## Motivation |
| The Pixtral-12B Vision Encoder module is designed for researchers and developers who: |
| - Require high-quality visual feature extraction |
| - Want to use the vision encoder independently of the full multimodal model |
| - Seek to implement custom downstream vision tasks |
| - Desire a lightweight, efficient vision representation module |
|
|
| ## Installation |
| ```python |
| from transformers import AutoModel |
| import torch |
| |
| # Load the vision encoder |
| vision_encoder = AutoModel.from_pretrained("your-repository/pixtral-12b-vision-encoder") |
| ``` |
|
|
| ## Example Usage |
| ```python |
| from PIL import Image |
| import torch |
| |
| # Load an image |
| image = Image.open("example_image.jpg") |
| |
| # Preprocess the image (ensure to use the corresponding processor) |
| inputs = vision_processor(images=image, return_tensors="pt") |
| |
| # Extract visual features |
| with torch.no_grad(): |
| visual_embeddings = vision_encoder(**inputs).last_hidden_state |
| |
| # Now you can use visual_embeddings for downstream tasks |
| ``` |
|
|
| ## Capabilities |
| - High-quality visual feature extraction |
| - Support for various image sizes |
| - Robust representation learning |
| - Compatible with multiple vision downstream tasks |
|
|
| ## Limitations |
| - Designed specifically for feature extraction |
| - Performance may vary depending on the specific downstream task |
| - Requires careful preprocessing and task-specific fine-tuning |
|
|
| ## Acknowledgements |
| Special thanks to the Mistral AI team for developing the original Pixtral-12B multimodal model. |
|
|
| ## License |
| Distributed under the Apache 2.0 License. |
|
|
| ## Citation |
| If you use this vision encoder in your research, please cite the original Mistral AI Pixtral-12B model. |
