Instructions to use sn56b2/70238e93-07e9-4592-ac02-fb558fb2fdcb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sn56b2/70238e93-07e9-4592-ac02-fb558fb2fdcb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "sn56b2/70238e93-07e9-4592-ac02-fb558fb2fdcb") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from sn56b2/70238e93-07e9-4592-ac02-fb558fb2fdcb: direct link, hf CLI and curl.
- Browser
- Download file 141 MB
-
https://huggingface.co/sn56b2/70238e93-07e9-4592-ac02-fb558fb2fdcb/resolve/main/adapter_model.bin
- Command line
-
hf download hf://sn56b2/70238e93-07e9-4592-ac02-fb558fb2fdcb/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/sn56b2/70238e93-07e9-4592-ac02-fb558fb2fdcb/resolve/main/adapter_model.bin
141 MB
- Xet hash:
- 84b33f46f4fe2e81fec5ed3a52e4663864f90e10405881be8ac6ae28b0426920
- Size of remote file:
- 141 MB
- SHA256:
- 1dfbaa1c087b2bb112f16eb61dd83ef3537bd9177bc8eb667c2be8cbbc82c992
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