clipseg-rd64-refined
CLIPSeg model with reduce dimension 64, refined (using a more complex convolution). It was introduced in the paper Image Segmentation Using Text and Image Prompts by Lüddecke et al. and first released in this repository.
Params
150 M
Context
—
Downloads 30d
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Likes
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Download history
daily snapshots · 106 days
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Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 0.6 GB | 1.2 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- CLIPSegForImageSegmentation
- Parameters
- 150 M
- Tensor type
- F32
- Licence
- apache-2.0
- First seen on the Hub
- 2022-11-01
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Compare with any image-segmentation model