Instructions to use beast33/5bd4e52a-1069-4c7f-a5c9-6901e92ca4a8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/5bd4e52a-1069-4c7f-a5c9-6901e92ca4a8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-1.7B") model = PeftModel.from_pretrained(base_model, "beast33/5bd4e52a-1069-4c7f-a5c9-6901e92ca4a8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0c945d17729bfb9050cc873885643417b2157de62da65f911cdd99735ec7416
- Size of remote file:
- 6.84 kB
- SHA256:
- 4e2b281a03db91986b426edd10b729c43ff4cd7cedd7b45dcbfdeb2fd2d00ca2
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