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πŸ€– Phi-3-Clinical

Welcome to the repository for Phi-3-Clinical, a fine-tuned model designed to empower medical researchers and developers in the Bio-Pharma domain. This model has been meticulously trained on clinical trial datasets from the U.S. government to deliver high-quality insights and facilitate research and development in healthcare and pharmaceutical innovation. This model is currently being actively updated and improved as part of my ongoing research and work in Retrieval-Augmented Generation (RAG).


πŸš€ Key Features

  • Fine-Tuned on: [Dataset(s) name]
  • Primary Use Case(s): [Summarization, Question Answering, etc.]
  • Updates in Progress:
    • Optimizing for better accuracy with RAG workflows.
    • Incorporating new datasets and training strategies.
    • Fine-tuning with community feedback.

πŸ“… What's Next?

I am actively working on:

  1. Integrating this model into a RAG pipeline for enhanced retrieval-augmented tasks.
  2. Regular updates to improve performance and reduce inference time.
  3. Expanding support for [languages/domains/etc.].

Stay tuned for updates and improvements in the coming weeks!


πŸ› οΈ How to Use

Here's a quick example of how you can use this model:

from transformers import pipeline

# Load the model
model = pipeline("task_name", model="hackint0sh/phi-3-clinical")

# Example usage
input_text = "Your input here"
output = model(input_text)
print(output)

Replace task_name with the appropriate task (e.g., "text-classification", "question-answering", "Clinical Trial Format").

πŸ™‹β€β™‚οΈ Need Help?

I’m here to help! If you have any questions, suggestions, or encounter any issues while using the model, feel free to: β€’ Open an Issue on this repository. β€’ DM me directly on Hugging Face.

I’m always happy to collaborate and improve this model further based on your feedback. 😊

🌟 Contributing

Contributions are welcome! If you have ideas for improvements or want to contribute, feel free to fork this repository and open a pull request.

πŸ“ License

This model is released under the MIT license. See the LICENSE file for more details.

Thank you for your interest in Phi-3-Clinical! Your support and feedback help make this model better for everyone. ❀️

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