Instructions to use viv6267/evaluation_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use viv6267/evaluation_model with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("NousResearch/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "viv6267/evaluation_model") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from viv6267/evaluation_model: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/viv6267/evaluation_model/resolve/main/training_args.bin
- Command line
-
hf download hf://viv6267/evaluation_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/viv6267/evaluation_model/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 9551b1cb1e080b2076981a89f8737a116dd59dd3ad4ca9c56a945841fe16bc4f
- Size of remote file:
- 5.37 kB
- SHA256:
- de8c5d5c3f90acf32f4a242d917b14d899039ddeb3dcd3cbfb4931598e6c6976
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