How to use from the
Use from the
Transformers library
# Load model directly
from transformers import NewModelForCL
model = NewModelForCL.from_pretrained("SparseCL/GTE-SparseCL-arguana", trust_remote_code=True, device_map="auto")
Quick Links

GTE-SparseCL-arguana

This repository contains a SparseCL model based on Alibaba-NLP/gte-large-en-v1.5 and trained on the Arguana dataset.

SparseCL is designed for contradiction retrieval.

For implementation and usage details, please see the SparseCL repository.

Citation

Please cite our paper if you use this model:

@inproceedings{xu2025contradiction,
  title={Contradiction Retrieval via Contrastive Learning with Sparsity},
  author={Xu, Haike and Lin, Zongyu and Chang, Kai-Wei and Sun, Yizhou and Indyk, Piotr},
  booktitle={International Conference on Machine Learning},
  year={2025}
}

license: mit

Downloads last month
13
Safetensors
Model size
0.4B params
Tensor type
F32
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support