mask2former-swin-large-ade-semantic
Mask2Former model trained on ADE20k semantic segmentation (large-sized version, Swin backbone). It was introduced in the paper Masked-attention Mask Transformer for Universal Image Segmentation and first released in this repository.
Params
220 M
Context
—
Downloads 30d
336 K
Likes
33
Download history
daily snapshots · 106 days
▲ 85 K in the last 30 days (20.2%)
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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 | 0.9 GB | 1.5 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
- Mask2FormerForUniversalSegmentation
- Parameters
- 220 M
- Tensor type
- F32
- Layers / heads
- 10 / 8
- Licence
- other
- First seen on the Hub
- 2023-01-05
- Training datasets
- coco
- Added to our catalog
- 2026-07-28
Compare with any image-segmentation model