Instructions to use beast33/184b72aa-aa89-4145-8ab7-7a4c1f39f1dc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/184b72aa-aa89-4145-8ab7-7a4c1f39f1dc with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama") model = PeftModel.from_pretrained(base_model, "beast33/184b72aa-aa89-4145-8ab7-7a4c1f39f1dc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 605181e5b22b04c1c66bec803a6bafe4dc10df78d11b01aac63cd6c155981a9b
- Size of remote file:
- 25.3 MB
- SHA256:
- b34695a361600443b6d5892b886b71cb21ed51dc15c56dc19593801bedc7eda0
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