Instructions to use genloop/FHIR_QnA_Relevance_Classification_Mistral-NeMo-BASE-FT_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_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_T1")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("genloop/FHIR_QnA_Relevance_Classification_Mistral-NeMo-BASE-FT_T1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag and library name
#1
by nielsr HF Staff - opened
This PR adds the metadata for the paper Question Answering on Patient Medical Records with Private Fine-Tuned LLMs.
The metadata includes the license, library name and pipeline tag.
Please review and merge this PR if everything looks good.
ayushgs changed pull request status to merged