Instructions to use kaierlong/gemma-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kaierlong/gemma-chinese with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b") model = PeftModel.from_pretrained(base_model, "kaierlong/gemma-chinese") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b267f7dd3a66351a407f7d6cd952736693655db5cd18c93f42832e9e5091a562
- Size of remote file:
- 4.92 kB
- SHA256:
- 7703ac49f9fb527e33cee21939547d1f4f77206077f77f00cc08f8f59a1f00ac
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