Instructions to use genloop/FHIR_QnA_Query-Based_Resource_Relevance_Classification_T1_complete with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use genloop/FHIR_QnA_Query-Based_Resource_Relevance_Classification_T1_complete with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="genloop/FHIR_QnA_Query-Based_Resource_Relevance_Classification_T1_complete")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("genloop/FHIR_QnA_Query-Based_Resource_Relevance_Classification_T1_complete", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| library_name: transformers | |
| pipeline_tag: question-answering | |
| 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). |