Instructions to use DataCleaning/Fine-tune-using-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DataCleaning/Fine-tune-using-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "DataCleaning/Fine-tune-using-LoRA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2038ec5a24d59e32aae7a51c6a7aad7d34247a5aca36b0bdd756c298b712122
- Size of remote file:
- 134 MB
- SHA256:
- 87ce04606e93db8a1b2415a4cc28fa02cd35aba841f4f3d4999e4971907ac564
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