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license: apache-2.0
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This repository hosts both the standard and quantized versions of the Zephyr 7B model, allowing users to choose the version that best fits their resource constraints and performance needs.

Model Details
Model Name: Zephyr 7B
Model Size: 7 billion parameters
Architecture: Transformer-based
Languages: Primarily English, with support for multilingual text
Quantized Version: Available for reduced memory footprint and faster inference

Performance and Efficiency
The quantized version of Zephyr 7B is optimized for environments with limited computational resources. It offers:

Reduced Memory Usage: The model size is significantly smaller, making it suitable for deployment on devices with limited RAM.
Faster Inference: Quantized models can perform faster inference, providing quicker responses in real-time applications.

Fine-Tuning
You can fine-tune the Zephyr 7B model on your own dataset to better suit specific tasks or domains. Refer to the Huggingface documentation for guidance on how to fine-tune transformer models.

Contributing
We welcome contributions to improve the Zephyr 7B model. Please submit pull requests or open issues for any enhancements or bugs you encounter.

License
This model is licensed under the MIT License.

Acknowledgments
Special thanks to the Huggingface team for providing the transformers library and to the broader AI community for their continuous support and contributions.

Contact
For any questions or inquiries, please contact us at akshayhedaoo7246@gmail.com.