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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f56b4429655c277aadaff70a90a7c681b97617f30f816a0f26424e9787f455ab
- Size of remote file:
- 3.51 MB
- SHA256:
- 835cf54bb933752267652500a9243a9002107bbb4501b99f8d2f46ccfdad2567
路
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