alivecat/clipseg-rd64-refined-mnn-wq8
image-segmentation model by alivecat
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Model card & documentation
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WQ8 MNN conversion of CIDAS/clipseg-rd64-refined for text-guided image segmentation. An image and a short text prompt produce a mask for the described region. Runtime: MNN (GitHub). Use an MNN runtime with batch size 1 as the documented input convention. Image inputs and exported logits use float32; fp32 in the filename identifies the source conversion variant. Tokenizer files, preprocessorconfig.json, and the upstream architecture config.json are included.…
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Model overview
alivecat/clipseg-rd64-refined-mnn-wq8 is a image-segmentation model repository published by alivecat on Hugging Face. A library was not reported.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-segmentation
- Library
- Not reported
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- CLIPSegForImageSegmentation
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-11-09T06:46:26.000Z
- Last modified
- 2026-11-09T06:46:49.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: CIDAS/clipseg-rd64-refined
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-09T06:55:49.891Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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