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:
- 24aecd80a882da81b9eb6eccbaae3711d2b506d534c4440d3a3b2190a053e958
- Size of remote file:
- 9.89 GB
- SHA256:
- 09c0622450bbf9960e5bf154388eff109b2c223b1ee96b1a71751f46e1d79e49
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