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/optimizer.pt from cimol/f7526a94-e690-4cf4-b3d9-bb77f3736062: direct link, hf CLI and curl.
- Browser
- Download file 21.7 MB
-
https://huggingface.co/cimol/f7526a94-e690-4cf4-b3d9-bb77f3736062/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://cimol/f7526a94-e690-4cf4-b3d9-bb77f3736062/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/cimol/f7526a94-e690-4cf4-b3d9-bb77f3736062/resolve/main/last-checkpoint/optimizer.pt
21.7 MB
- Xet hash:
- 05e0a7a624e5573880e009bd7e90588029ce3d27bcabe896b79819db557ee7eb
- Size of remote file:
- 21.7 MB
- SHA256:
- d57935fa15c96a1643ffadf083c34db8a9d30de17b6da53e15140bebbff72098
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