Instructions to use UCSC-VLAA/MedReason-Mistral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UCSC-VLAA/MedReason-Mistral with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="UCSC-VLAA/MedReason-Mistral")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UCSC-VLAA/MedReason-Mistral", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card: Add library name and pipeline tag
#1
by nielsr HF Staff - opened
This PR improves the model card by adding the library_name and pipeline_tag metadata. The library_name is set to transformers based on the provided usage example. The pipeline_tag is set to question-answering as per the paper abstract and prompt. Additionally, the content from the Github README has been incorporated to provide more comprehensive information about the model, data, training, and evaluation.
thanks
cihangxie changed pull request status to merged