Instructions to use cimol/f7526a94-e690-4cf4-b3d9-bb77f3736062 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/f7526a94-e690-4cf4-b3d9-bb77f3736062 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("facebook/opt-125m") model = PeftModel.from_pretrained(base_model, "cimol/f7526a94-e690-4cf4-b3d9-bb77f3736062") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/adapter_model.safetensors from cimol/f7526a94-e690-4cf4-b3d9-bb77f3736062: direct link, hf CLI and curl.
- Browser
- Download file 42.5 MB
-
https://huggingface.co/cimol/f7526a94-e690-4cf4-b3d9-bb77f3736062/resolve/main/last-checkpoint/adapter_model.safetensors
- Command line
-
hf download hf://cimol/f7526a94-e690-4cf4-b3d9-bb77f3736062/last-checkpoint/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/cimol/f7526a94-e690-4cf4-b3d9-bb77f3736062/resolve/main/last-checkpoint/adapter_model.safetensors
42.5 MB
- Xet hash:
- 1a4a1159e6a8ebfaa6dee405c38ea39878085e04bd9ba2d4f6e79180689165aa
- Size of remote file:
- 42.5 MB
- SHA256:
- 09802372ae6528ae60ef4239d9054890cac2425f1ea418a31b103f78903f12df
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.