Instructions to use phdatdt/binary_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use phdatdt/binary_classification with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "phdatdt/binary_classification") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from phdatdt/binary_classification: direct link, hf CLI and curl.
- Browser
- Download file 54.6 MB
-
https://huggingface.co/phdatdt/binary_classification/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://phdatdt/binary_classification/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/phdatdt/binary_classification/resolve/main/adapter_model.safetensors
54.6 MB
- Xet hash:
- ae6024a4f456ebe4c95010bf4a49190bb15b7fa6fcd2be8749ae9622e7f72576
- Size of remote file:
- 54.6 MB
- SHA256:
- dda02235deca4f207fc70e37c4c6db7802a7a688e20ff493a040c04d9988d504
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