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OpenSportsLab/OSL-VQA-XFOUL-qwen2.5-7B-VL-lora

sourceHugging Faceagpl-3.0updated 2mo agoView on Hugging Face
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Model Card

OpenSportsLib VQA Model (Qwen2.5-VL LoRA)

Overview

This model is a VQA LoRA adapter produced with OpenSportsLib for soccer foul understanding and referee-style visual question answering.

  • —Task: Visual Question Answering (VQA)
  • —Architecture: Qwen2.5-VL + LoRA adapter
  • —Backend: qwen_vl_native_lora
  • —Base model: Qwen/Qwen2.5-VL-7B-Instruct
  • —Library: OpenSportsLib
  • —Input: Soccer video clips plus natural-language questions
  • —Visual path: Native end-to-end QwenVL video understanding

Dataset

Training Dataset

This adapter was trained on the OpenSportsLib XFoul VQA setup built on the OSL-XFoul dataset.

  • —Dataset name: OSL-XFoul
  • —Domain: Soccer video understanding and officiating
  • —Task: Visual question answering
  • —Modality: Video + text
  • —Training samples: 16,568
  • —Validation samples: 2,219

Benchmark Results

AccuracyBalanced Accuracy
65.77%36.59%

Using with OpenSportsLib

For more details about OpenSportsLib:

  • —GitHub: https://github.com/OpenSportsLab/opensportslib
  • —PyPI: https://pypi.org/project/opensportslib/
  • —Documentation: https://opensportslab.github.io/opensportslib/

Run inference

python
from opensportslib.apis import VQAModel

my_model = VQAModel(
    config="opensportslib/configs/vqa/qwen3_vl_native.yaml",
    weights="YOUR_HF_REPO_ID",
)

predictions = my_model.infer(
    test_set="/path/to/test_annotations.json",
)

single_prediction = my_model.infer(
    video_path="/path/to/video.mp4",
    question="Was this a foul? What card should be given?",
)

print(predictions)
print(single_prediction)

Notes

  • —This repository stores a PEFT LoRA adapter, not a merged standalone base model.
  • —The adapter is intended for the OpenSportsLib native QwenVL VQA path driven by opensportslib/configs/vqa/qwen3_vl_native.yaml.
  • —The original training setup used frame-based native multimodal inputs with Qwen/Qwen2.5-VL-7B-Instruct.

License

  • —Open source license: AGPL 3.0 for research, academic, and community use.
  • —Commercial license: For proprietary or commercial deployment, please contact the project maintainers.

Citation

bibtex
@misc{opensportslib_qwen25_vl_vqa_xfoul_lora_2026,
  title={OpenSportsLib Qwen2.5-VL LoRA for Soccer VQA},
  author={OpenSportsLab},
  year={2026},
  howpublished={https://huggingface.co/OpenSportsLab}
}

Acknowledgements

  • —Dataset: OpenSportsLab / OSL-XFoul
  • —Library: https://github.com/OpenSportsLab/opensportslib
  • —Model pipeline: OpenSportsLib native QwenVL VQA backend