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:
- 8cbcd44f19f9fbb70f336b6ee1ec5b0706616dee9f09ad62d269fb505fb42817
- Size of remote file:
- 3.5 GB
- SHA256:
- 0fd6895090da1b2ccffdb93964847709a3b31e6b69fe7dc5a480dce37c811b1d
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