Instructions to use Jeesup/llama32-3B-rte-nf4-lora-seed42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Jeesup/llama32-3B-rte-nf4-lora-seed42 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B") model = PeftModel.from_pretrained(base_model, "Jeesup/llama32-3B-rte-nf4-lora-seed42") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70bba26331cd51f68a8ae5c1e9dfe0bd2fcc781f40395ca1d005ad82a2ee8b56
- Size of remote file:
- 36.7 MB
- SHA256:
- 8b13c25f6329f48de3218a38e46157e6bb3f5e918bd1d6c265ce9171b5ea45e4
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