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:
- 09f7347aec56181683d0b3fc67ef5baa26b844b316c262e33dcce98ea784486f
- Size of remote file:
- 1.59 MB
- SHA256:
- 89ff9c67364c833920c7d7877da1b2d2173b8baf7b64b46299114f1d494ecc13
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