Instructions to use lhong4759/820f096e-fef4-457f-8928-a303a965f42e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lhong4759/820f096e-fef4-457f-8928-a303a965f42e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-1.7B") model = PeftModel.from_pretrained(base_model, "lhong4759/820f096e-fef4-457f-8928-a303a965f42e") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from lhong4759/820f096e-fef4-457f-8928-a303a965f42e: direct link, hf CLI and curl.
- Browser
- Download file 36.3 MB
-
https://huggingface.co/lhong4759/820f096e-fef4-457f-8928-a303a965f42e/resolve/main/adapter_model.bin
- Command line
-
hf download hf://lhong4759/820f096e-fef4-457f-8928-a303a965f42e/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/lhong4759/820f096e-fef4-457f-8928-a303a965f42e/resolve/main/adapter_model.bin
36.3 MB
- Xet hash:
- 9bc935809bc64a626b712e021d70f1d6d74a1b6053f1036a958db7e0b3c51d67
- Size of remote file:
- 36.3 MB
- SHA256:
- 1588b6af1fe80cbc3afd4f6291a5f2006ada51329783294eb2f3fc88f3fc0279
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