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:
- 309aa28dff7a36e894f7d325c08e0d758d58b5721b47b77d497307cc26d73b92
- Size of remote file:
- 289 MB
- SHA256:
- db1356b3ef47f4fdc142241f07275927bf32753895806b94d2df0e4f2ded1004
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