Instructions to use tmnam20/Llama-3.2-1B-Instruct-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tmnam20/Llama-3.2-1B-Instruct-SFT with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tmnam20/Llama-3.2-1B-Instruct-SFT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tmnam20/Llama-3.2-1B-Instruct-SFT: direct link, hf CLI and curl.
- Browser
- Download file 5.56 kB
-
https://huggingface.co/tmnam20/Llama-3.2-1B-Instruct-SFT/resolve/main/training_args.bin
- Command line
-
hf download hf://tmnam20/Llama-3.2-1B-Instruct-SFT/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tmnam20/Llama-3.2-1B-Instruct-SFT/resolve/main/training_args.bin
5.56 kB
- Xet hash:
- b0dd136db3412d96ac8bafe7bee4e68ff153c4b1f778d3c38f1efa67e6ce0908
- Size of remote file:
- 5.56 kB
- SHA256:
- 1ec25389d8b7f46f5900e0474ed789088575121712f93d34b2a08cef97adb644
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