Instructions to use antimage88/80b65fd5-a25c-415a-a2f7-da7e72bee688 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use antimage88/80b65fd5-a25c-415a-a2f7-da7e72bee688 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-135M-Instruct") model = PeftModel.from_pretrained(base_model, "antimage88/80b65fd5-a25c-415a-a2f7-da7e72bee688") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from antimage88/80b65fd5-a25c-415a-a2f7-da7e72bee688: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/antimage88/80b65fd5-a25c-415a-a2f7-da7e72bee688/resolve/078a355b00f784196d1ae23cd4392684addecab3/training_args.bin
- Command line
-
hf download hf://antimage88/80b65fd5-a25c-415a-a2f7-da7e72bee688@078a355b00f784196d1ae23cd4392684addecab3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/antimage88/80b65fd5-a25c-415a-a2f7-da7e72bee688/resolve/078a355b00f784196d1ae23cd4392684addecab3/training_args.bin
6.84 kB
- Xet hash:
- 7e2aa082ae83fafb6a631a851b7ea33ed0f2e94c2eaf8330afcfe4a3de3d5f4d
- Size of remote file:
- 6.84 kB
- SHA256:
- 3a2811eaef6e4e80237597cbd26fa2d4083258f08ba0096e6da5feadd756cd1e
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