Instructions to use genloop/FHIR_QnA_Relevance_Classification_Mistral-Nemo-Base-FT_T2_T1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use genloop/FHIR_QnA_Relevance_Classification_Mistral-Nemo-Base-FT_T2_T1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="genloop/FHIR_QnA_Relevance_Classification_Mistral-Nemo-Base-FT_T2_T1")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("genloop/FHIR_QnA_Relevance_Classification_Mistral-Nemo-Base-FT_T2_T1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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# Model Card for Model ID
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** Genloop
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- **Funded by:** Genloop
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### Model Sources [optional]
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- **Paper:** arxiv.org/abs/2501.14249
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# Model Card for Model ID
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This repository contains the model introduced in the paper [Question Answering on Patient Medical Records with Private Fine-Tuned LLMs](https://huggingface.co/papers/2501.13687).
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