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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("CodCodingCode/llama-clinical-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from CodCodingCode/llama-clinical-lora: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/CodCodingCode/llama-clinical-lora/resolve/7b5a31442f8f6b06c4f2d9db76d5a594b8e83de4/tokenizer.json
- Command line
-
hf download hf://CodCodingCode/llama-clinical-lora@7b5a31442f8f6b06c4f2d9db76d5a594b8e83de4/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/CodCodingCode/llama-clinical-lora/resolve/7b5a31442f8f6b06c4f2d9db76d5a594b8e83de4/tokenizer.json
17.2 MB
- Xet hash:
- 0fe0317133d131441e446cd553bfecfda7baeff9330c9b6d795d1a4d696fe1f2
- Size of remote file:
- 17.2 MB
- SHA256:
- a9d4fd2d4afa82d8a7dadae3490fdc20b26f06e32cec78a8dc96521b4dc79038
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