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:
- c99196affe4c7e698f12f04c264a087aa72ec6fa7a6d72e6c67e9ae55470c74d
- Size of remote file:
- 9.98 GB
- SHA256:
- 66dec18c9f1705b9387d62f8485f4e7d871ca388718786737ed3c72dbfaac9fb
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