Instructions to use beast33/b8d58659-a4a3-4650-b1f4-982f37ec1873 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/b8d58659-a4a3-4650-b1f4-982f37ec1873 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-135M") model = PeftModel.from_pretrained(base_model, "beast33/b8d58659-a4a3-4650-b1f4-982f37ec1873") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a740481c7db80e44c325c85f82a1601f0e76df68a079df7b35e172db197ccfa
- Size of remote file:
- 9.82 MB
- SHA256:
- 585e33b6dab931762cfa2c255ef5f9bc9be62cc8359ee7ac88111b8d7aeaa567
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