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 # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="genloop/FHIR_QnA_Query-Based_Resource_Relevance_Classification_T1_complete")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("genloop/FHIR_QnA_Query-Based_Resource_Relevance_Classification_T1_complete", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add model card metadata
#1
by nielsr HF Staff - opened
This PR adds the pipeline_tag as well as the library_name to ensure proper functionality in the Hugging Face ecosystem. It also adds the license according to the best available information.
ayushgs changed pull request status to merged