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:
- 23c8008017527986fd300f3362c4a6c5b4c23b93bae4a0a8d5781882ccabfc90
- Size of remote file:
- 414 Bytes
- SHA256:
- 6fa06efa2785e450051989a6f8fb4416b10149ded485ddd3f127a40734f5cfd0
路
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