Instructions to use MatanP/LLAMA_fine_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MatanP/LLAMA_fine_tuned 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, "MatanP/LLAMA_fine_tuned") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from MatanP/LLAMA_fine_tuned: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/MatanP/LLAMA_fine_tuned/resolve/main/training_args.bin
- Command line
-
hf download hf://MatanP/LLAMA_fine_tuned/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/MatanP/LLAMA_fine_tuned/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- eb651632fec4431843a9b5c160c59bfe7aecab65a4602296982ad98eef7aeb0a
- Size of remote file:
- 5.5 kB
- SHA256:
- 54fe1298f4f438ac9f4ad8e9bf9cc467c7326ad5280014fdbd2544478c5f6979
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