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:
- ada6ca67ebfbe2e3a8688d2847a27a289370272ad1092f6eec6b18e9cb29e7ee
- Size of remote file:
- 9.88 GB
- SHA256:
- 7817162c438c935c31b8db599fa43a9fcf938bdccfdd8b3da0af5c185aa5c9ee
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