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---
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.