Instructions to use lmong/Adapter3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lmong/Adapter3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-4k-instruct") model = PeftModel.from_pretrained(base_model, "lmong/Adapter3") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lmong/Adapter3: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/lmong/Adapter3/resolve/main/training_args.bin
- Command line
-
hf download hf://lmong/Adapter3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lmong/Adapter3/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- f86788eae2dfb2addcfa9083048aca2677a0978391629c9941b1cfd7b4f840c1
- Size of remote file:
- 5.5 kB
- SHA256:
- 421fc059333f632156669132eaa01e2d230f01bd0d7a74bec16779c384cc5550
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