Instructions to use Tirendaz/llama-2-7b-chat-guanaco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Tirendaz/llama-2-7b-chat-guanaco with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "Tirendaz/llama-2-7b-chat-guanaco") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67c90d6041951773213dedc8ad90a495da82a56ad57a45f7483f153a3092b9ac
- Size of remote file:
- 134 MB
- SHA256:
- 03eb367daacdabbf9f4d2b1494fc9cfcc737ff85652f2ce0b12434917782b1c9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.