Instructions to use mrHungddddh/bdaeefc5-1cc3-4924-a8a7-ea19648b6ec1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mrHungddddh/bdaeefc5-1cc3-4924-a8a7-ea19648b6ec1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("EleutherAI/pythia-70m-deduped") model = PeftModel.from_pretrained(base_model, "mrHungddddh/bdaeefc5-1cc3-4924-a8a7-ea19648b6ec1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d6fd2b15ca0f165d06c74ef9787f5f00a13b9ce15091b7f50c0f1b2fd98a68a
- Size of remote file:
- 6.78 kB
- SHA256:
- fc8174e709ae1ce11005aa2151a866a31eaf4640aa7cd9198c8e6846968e3651
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.