Instructions to use cimol/ad3bc1b8-ba08-4f1f-98a9-69fdbae7884b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/ad3bc1b8-ba08-4f1f-98a9-69fdbae7884b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-3B") model = PeftModel.from_pretrained(base_model, "cimol/ad3bc1b8-ba08-4f1f-98a9-69fdbae7884b") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from cimol/ad3bc1b8-ba08-4f1f-98a9-69fdbae7884b: direct link, hf CLI and curl.
- Browser
- Download file 389 MB
-
https://huggingface.co/cimol/ad3bc1b8-ba08-4f1f-98a9-69fdbae7884b/resolve/main/adapter_model.bin
- Command line
-
hf download hf://cimol/ad3bc1b8-ba08-4f1f-98a9-69fdbae7884b/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/cimol/ad3bc1b8-ba08-4f1f-98a9-69fdbae7884b/resolve/main/adapter_model.bin
389 MB
- Xet hash:
- 99ccfc00c66a90847e0c40f3d6efdf6468cf7113422bb4e220e3558caa703ef0
- Size of remote file:
- 389 MB
- SHA256:
- 8c9a464a4a6b8acd88603479bef9ac0634ff02ab53a73c76757ea871f16c292b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.