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:
- 5ae1febf9bc7f2de095bfbfe41d458585b101d908e1f1cf3c1dbf980f82b6221
- Size of remote file:
- 7.18 GB
- SHA256:
- bbc0ea1c0c288aa38ad082b4691fe477f850ecd07aa3ed6015b8c549eb5a080b
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