Instructions to use thangla01/60c4c099-ddda-452d-9b89-5c0d5e547cd3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thangla01/60c4c099-ddda-452d-9b89-5c0d5e547cd3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-360M") model = PeftModel.from_pretrained(base_model, "thangla01/60c4c099-ddda-452d-9b89-5c0d5e547cd3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b659c26cfbaf710ba4137070fc06c9cb1a6a00f2a67c042ffd6eee302c5859b
- Size of remote file:
- 6.78 kB
- SHA256:
- 5965cad306021335ce11086a2fc601c4277eebd3142ebf215cdbfe6d9f02647f
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