Instructions to use thangla01/5d31beb4-1dd4-4364-b08b-46fbd57271a7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thangla01/5d31beb4-1dd4-4364-b08b-46fbd57271a7 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, "thangla01/5d31beb4-1dd4-4364-b08b-46fbd57271a7") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1358b69c7ed1fd9497e682019c3a2fa0c0990ab2574d14f039cda263f738042e
- Size of remote file:
- 6.78 kB
- SHA256:
- 3cda0d2a1994323620a29e72d2d7f43e10509fa63425e4d4ec7b0bfb5eacb051
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