Instructions to use eeeebbb2/95dfc0fc-2086-4e04-9017-9cb7cfd75afa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/95dfc0fc-2086-4e04-9017-9cb7cfd75afa with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("llamafactory/tiny-random-Llama-3") model = PeftModel.from_pretrained(base_model, "eeeebbb2/95dfc0fc-2086-4e04-9017-9cb7cfd75afa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1764001543899106a3168f0d55a6a527fadce55b617f89242903ae4ace0ef8d
- Size of remote file:
- 17.2 MB
- SHA256:
- 3c5cf44023714fb39b05e71e425f8d7b92805ff73f7988b083b8c87f0bf87393
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