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README.md
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Installation
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To use this model, you first need to install the required packages. Run the following command:
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bash
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Copy code
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pip install -r requirements.txt
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Usage
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Here's how to use the model in your project:
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python
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from transformers import AutoModel, AutoTokenizer
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model_name = "your-huggingface-model-identifier"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModel.from_pretrained(model_name)
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def predict(text):
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inputs = tokenizer(text, return_tensors="pt")
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with torch.no_grad():
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logits = model(**inputs).logits
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predicted_class_id = logits.argmax().item()
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return model.config.id2label[predicted_class_id]
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# Example usage
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text = "Your example text here"
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print(predict(text))
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Performance
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Discuss the performance metrics, benchmarks, or comparisons here, showing how the model performs in various scenarios.
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Contributing
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We welcome contributions to improve the model or scripts. Please follow these steps to contribute:
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Fork the repository.
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Create a new branch (git checkout -b feature-branch).
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Commit your changes (git commit -am 'Add some feature').
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Push to the branch (git push origin feature-branch).
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Open a new Pull Request.
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License
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This project is licensed under the [choose a license] - see the LICENSE file for details.
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Citation
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If you use this model in your research, please cite it as follows:
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bibtex
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@inproceedings{author2023model,
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title={Title of Your Model},
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author={Author Names},
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booktitle={Where it was published},
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year={2023}
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}
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Acknowledgments
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Mention any advisors, financial supporters, or data providers.
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Any other recognition or credits.
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Contact
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For issues, questions, or collaborations, you can contact [email contact] or create an issue in this repository.
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---
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title: ask-ASH
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emoji: "🏥"
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colorFrom: pink
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colorTo: red
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sdk: streamlit
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sdk_version: 1.33.0
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app_file: app.py
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pinned: false
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---
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