Instructions to use eeeebbb2/86eaa4ce-fd20-4d44-b116-393da232106b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/86eaa4ce-fd20-4d44-b116-393da232106b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-1B") model = PeftModel.from_pretrained(base_model, "eeeebbb2/86eaa4ce-fd20-4d44-b116-393da232106b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88ea2574a6cb96bbfa2d23df27769c5c99f23a4f37e1d6550cd68180ded492c8
- Size of remote file:
- 90.2 MB
- SHA256:
- 1c9454fc1015cb5439abcfd78f378b75e901f4dc3b892174138501d1cfe61dab
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