Seg2Click-Qwen3.5-4B
Seg2Click predicts a pixel-level action mask from a screenshot and an instruction, then selects a click at the centroid of the largest connected foreground component.
Paper: https://arxiv.org/abs/2610.16234
Code and installation instructions: https://github.com/jcwang0602/Seg2Click
Contents
This checkpoint includes the merged backbone, the FP32 action-mask decoder, and the tokenizer and processor required for inference. LoRA is already merged; no separate adapter should be applied.
Inference
Install Seg2Click and its dependencies, then download the public checkpoint:
from huggingface_hub import snapshot_download
from PIL import Image
from seg2click.predictor import Seg2ClickPredictor
checkpoint = snapshot_download("jcwang0602/Seg2Click-Qwen3.5-4B")
predictor = Seg2ClickPredictor.from_pretrained(checkpoint)
prediction = predictor.predict(Image.open("screenshot.png"), "close this window")
print(prediction.point) # normalized (x, y) in the original screenshot
The custom decoder requires the Seg2Click inference code. Loading the backbone alone with a generic Transformers generation pipeline does not perform mask-to-click prediction.
License
This model is fine-tuned from Qwen/Qwen3.5-4B.
The backbone license is included in LICENSE; it is distinct from the MIT license
of the Seg2Click source code.
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