Instructions to use eeeebbb2/ed54852c-5ead-4e2d-8aea-30994891c5ad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/ed54852c-5ead-4e2d-8aea-30994891c5ad with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-360M") model = PeftModel.from_pretrained(base_model, "eeeebbb2/ed54852c-5ead-4e2d-8aea-30994891c5ad") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f04cee420e9f0d759c43cb964025e5b21f5ffba0609f02d6bf244e000d2c22f4
- Size of remote file:
- 6.84 kB
- SHA256:
- 332481211f5a5fa37a04b7097dc28a188770f4264716bb3591ecd58f79715865
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