Instructions to use hongngo/cc9e7333-318f-4147-9540-cc0b938b8e24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hongngo/cc9e7333-318f-4147-9540-cc0b938b8e24 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Hermes-3-Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "hongngo/cc9e7333-318f-4147-9540-cc0b938b8e24") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hongngo/cc9e7333-318f-4147-9540-cc0b938b8e24: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/hongngo/cc9e7333-318f-4147-9540-cc0b938b8e24/resolve/main/training_args.bin
- Command line
-
hf download hf://hongngo/cc9e7333-318f-4147-9540-cc0b938b8e24/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hongngo/cc9e7333-318f-4147-9540-cc0b938b8e24/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 1a730a56e6a8b0d5aa787e3b25445ebf93b1cac04367df9123533d8130c98402
- Size of remote file:
- 6.78 kB
- SHA256:
- 9d43a95da0a38cea816ab21f127b44e37eb961c15ee50b648cea510bdf36273c
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