Instructions to use gavrilstep/6dacc36d-e42d-4b76-8b54-7ebbf26b9c1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gavrilstep/6dacc36d-e42d-4b76-8b54-7ebbf26b9c1b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("elyza/Llama-3-ELYZA-JP-8B") model = PeftModel.from_pretrained(base_model, "gavrilstep/6dacc36d-e42d-4b76-8b54-7ebbf26b9c1b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b0b356eae46c191152925da47d41219de736dc83f91d558fa24c0bf5d65978a
- Size of remote file:
- 503 MB
- SHA256:
- 76bdef3d7c6c6678f8ae8b2e8ec19d4d36432be01978c1c09048e58381d06e41
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