Instructions to use jazzson/adl-hw3-finetune-gemma-2-chinese-kyara-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jazzson/adl-hw3-finetune-gemma-2-chinese-kyara-3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("zake7749/gemma-2-2b-it-chinese-kyara-dpo") model = PeftModel.from_pretrained(base_model, "jazzson/adl-hw3-finetune-gemma-2-chinese-kyara-3") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jazzson/adl-hw3-finetune-gemma-2-chinese-kyara-3: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/jazzson/adl-hw3-finetune-gemma-2-chinese-kyara-3/resolve/main/training_args.bin
- Command line
-
hf download hf://jazzson/adl-hw3-finetune-gemma-2-chinese-kyara-3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jazzson/adl-hw3-finetune-gemma-2-chinese-kyara-3/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 2d33c0857506cb4a5742e4f4a6ce49aab98c94120fcf83cabec0fb495ec72bf2
- Size of remote file:
- 5.24 kB
- SHA256:
- 79b84696a998616f03e0506a675f60c5071c66dc977e26ae2beb33281837e8d0
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