Instructions to use Manab/LoRAImplement with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Manab/LoRAImplement with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigscience/bloom-1b7") model = PeftModel.from_pretrained(base_model, "Manab/LoRAImplement") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab4c7f15179469f0ac11141e996cdb0420976146039de2b40425fa878ef85aa4
- Size of remote file:
- 6.31 MB
- SHA256:
- b6bf4b0bf4b757bd7b305c3dc8e53141a68377b36ea459e4301c1ca81c4fd4a1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.