Instructions to use osbm/llama-7b-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use osbm/llama-7b-4bit with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("baffo32/decapoda-research-llama-7B-hf") model = PeftModel.from_pretrained(base_model, "osbm/llama-7b-4bit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f286e554e6d5a1ff0527887f05a41ad6d1a8c38d90c0bf0a635a1dfdcb255b0f
- Size of remote file:
- 16.8 MB
- SHA256:
- 3ebf99b0ff3a676d5bbb955dba3f83a04a4b143f2dc4c9c68fa8d027dde52d10
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.