Instructions to use CodCodingCode/llama-clinical-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodCodingCode/llama-clinical-lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("CodCodingCode/llama-clinical-lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34897cc625a1423a32fd40797691281fe3bfdd4b493e92be6083c0f2139f6495
- Size of remote file:
- 168 MB
- SHA256:
- f551276ae1a5b3b6dee019c25d5fb91ee04afd8434e56940fc702a2a0a30af99
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.