Instructions to use strumber/Llama2letsmod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use strumber/Llama2letsmod 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, "strumber/Llama2letsmod") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-200/optimizer.pt from strumber/Llama2letsmod: direct link, hf CLI and curl.
- Browser
- Download file 269 MB
-
https://huggingface.co/strumber/Llama2letsmod/resolve/main/checkpoint-200/optimizer.pt
- Command line
-
hf download hf://strumber/Llama2letsmod/checkpoint-200/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/strumber/Llama2letsmod/resolve/main/checkpoint-200/optimizer.pt
269 MB
- Xet hash:
- 8e57eb46ce369d43635e73d58a02923f8c9d9d90c3e2968c35f904fad0335fa4
- Size of remote file:
- 269 MB
- SHA256:
- 2f53ca70f4c68b7f9c7133c4e1d7c1480048d1dfd6f115acde27b0ac43d1bb23
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.