Instructions to use qanastek/MedAlpaca-LLaMa2-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use qanastek/MedAlpaca-LLaMa2-7B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "qanastek/MedAlpaca-LLaMa2-7B") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from qanastek/MedAlpaca-LLaMa2-7B: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/qanastek/MedAlpaca-LLaMa2-7B/resolve/main/adapter_model.bin
- Command line
-
hf download hf://qanastek/MedAlpaca-LLaMa2-7B/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/qanastek/MedAlpaca-LLaMa2-7B/resolve/main/adapter_model.bin
134 MB
- Xet hash:
- 447969f5ed6a171113bb9f7653f451cd48e5310e468f6f84a5d1b36c5651287e
- Size of remote file:
- 134 MB
- SHA256:
- 51eecc3e1cfd2cdf9266ba09f9ede9a0f77dc2f91f55f26378e5d369e7566073
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