Instructions to use dzanbek/8054c77e-296b-4b00-9027-00a93be11f9e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/8054c77e-296b-4b00-9027-00a93be11f9e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("OpenBuddy/openbuddy-llama2-13b-v8.1-fp16") model = PeftModel.from_pretrained(base_model, "dzanbek/8054c77e-296b-4b00-9027-00a93be11f9e") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from dzanbek/8054c77e-296b-4b00-9027-00a93be11f9e: direct link, hf CLI and curl.
- Browser
- Download file 125 MB
-
https://huggingface.co/dzanbek/8054c77e-296b-4b00-9027-00a93be11f9e/resolve/main/adapter_model.bin
- Command line
-
hf download hf://dzanbek/8054c77e-296b-4b00-9027-00a93be11f9e/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/dzanbek/8054c77e-296b-4b00-9027-00a93be11f9e/resolve/main/adapter_model.bin
125 MB
- Xet hash:
- 747dc3d875f5df85bdc9446ca1965461cb2d2a85f80e1fca4e3449a734c8bf03
- Size of remote file:
- 125 MB
- SHA256:
- 5c7e7d2bb52c8a1929b773876617da054359830c40a78101e359ce4a969b13d4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.