Multimodal JEV is a visual judgment model based on Qwen3.5-4B. It evaluates questions about images and returns structured judgments and probabilities rather than generating free-form answers. The checkpoint includes model weights, decision and ordinal heads, tokenizer, image processor, configuration and calibration metadata. Weights are stored in six indexed safetensors shards, totaling approximately 9.7 GiB. Inference requires the custom UnifiedJev loader, the mso runtime modules and their Python dependencies. These must be available on your Python import path; downloading the checkpoint alone is not sufficient. Standard Qwen loading does not implement the JEV judgment interface. The…
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Joebu
joebumodels
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