Instructions to use scottshan/story with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use scottshan/story with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-3-1b-pt") model = PeftModel.from_pretrained(base_model, "scottshan/story") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from scottshan/story: direct link, hf CLI and curl.
- Browser
- Download file 6.03 kB
-
https://huggingface.co/scottshan/story/resolve/main/training_args.bin
- Command line
-
hf download hf://scottshan/story/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/scottshan/story/resolve/main/training_args.bin
6.03 kB
- Xet hash:
- eb07006d7b3e12052080f97e741a1fa2e5b8d7e149589bbdfa91e4f32d4549b3
- Size of remote file:
- 6.03 kB
- SHA256:
- 9d75af18d6cc472bcb1d7ba320a2bd18104bad4cae0af966a53f766766715450
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