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:
- 01a8d747028209ebd09f35fafa21775e1c43456740ac33f1dcff349ec8c82b52
- Size of remote file:
- 15 kB
- SHA256:
- 6b8aa78776a3dab5938d269ec2dabb8fe56792ac8910da57598cd3925d55f156
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