Loading

This checkpoint inherits the architecture of Qwen/Qwen2.5-VL-3B-Instruct. You can load it using the standard transformers interface:

python
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from transformers import Qwen2_5_VLForConditionalGeneration, AutoProcessor
import torch

model_id = "ch-min/Qwen2.5-VL-3B-Instruct-data_scale_exp_80k-20251114_120221" # Replace with the actual repository ID
model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
    model_id, torch_dtype="auto", device_map="auto"
)
processor = AutoProcessor.from_pretrained(model_id)

# For inference, follow the standard Qwen2.5-VL usage pattern

Citation

If you use this checkpoint, please cite both our paper and the original Qwen2.5-VL-3B paper.

Our paper (this checkpoint family):

bibtex
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@article{min2026whyfarlooksup,
  title   = {Why Far Looks Up: Probing Spatial Representation in Vision-Language Models},
  author  = {Min, Cheolhong and Jung, Jaeyun and Lee, Daeun and Jeon, Hyeonseong and
             Su, Yu and Tremblay, Jonathan and Song, Chan Hee and Park, Jaesik},
  journal = {arXiv preprint arXiv:2605.30161},
  year    = {2026},
}

Original Qwen2.5-VL-3B (Qwen2.5-VL Technical Report):

bibtex
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@article{bai2025qwen25vl,
  title   = {Qwen2.5-VL Technical Report},
  author  = {Bai, Shuai and Chen, Keqin and Liu, Xuejing and Wang, Jialin and others},
  journal = {arXiv preprint arXiv:2502.13923},
  year    = {2025},
}