Instructions to use UCSC-VLAA/MedReason-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UCSC-VLAA/MedReason-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="UCSC-VLAA/MedReason-8B")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UCSC-VLAA/MedReason-8B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag, library name, data access, data generation, training pipeline and evaluation
#1
by nielsr HF Staff - opened
This PR adds the pipeline_tag and library_name to the model card metadata.
The pipeline_tag is set to question-answering to accurately reflect the model's capabilities.
The library_name is set to transformers as per the usage example code.
This PR adds data access, data generation, training pipeline and evaluation from the Github README to the model card.
This PR adds the images from the Github README to the model card.
thanks
cihangxie changed pull request status to merged