Instructions to use FatCat87/f10bdf17-9e76-43d8-9e0e-0b65ee5e0e98 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FatCat87/f10bdf17-9e76-43d8-9e0e-0b65ee5e0e98 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Coder-7B") model = PeftModel.from_pretrained(base_model, "FatCat87/f10bdf17-9e76-43d8-9e0e-0b65ee5e0e98") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3289def6e6172fedb158275ca04328ae5c82552983b512ed2d58b9dfce856616
- Size of remote file:
- 323 MB
- SHA256:
- 1299afba69c39984a21930e04c6e1c1b4999ce3a26a06908fe255780298a8dc2
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