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Open-weight model · Image segmentation
by Mateusz Dziemian mattmdjaga/segformer_b2_clothes
segformer_b2_clothes is an open-weight model for image segmentation from Mateusz Dziemian, released under other. It has 27M parameters. At 16-bit it needs about 0.1 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index. It draws 214.2k downloads a month.
SegFormer model fine-tuned on ATR dataset for clothes segmentation but can also be used for human segmentation. The dataset on hugging face is called "mattmdjaga/humanparsingdataset".
What it takes to serve segformer_b2_clothes (27M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.
| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
|---|---|---|---|---|---|
| 16-bit | 0.1 GB | 0.1 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 0.0 GB | 0.0 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 0.0 GB | 0.0 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 16, 2026.
segformer_b2_clothes on every accelerator the SAVRN Index prices, at every precision
This SegFormer model labels clothing and body parts pixel by pixel: hat, hair, sunglasses, upper clothes, skirt, pants, shoes, bags and more. It was trained on the ATR human parsing dataset and has 27M parameters.
The license is listed as other, so check the terms and the terms of the NVIDIA SegFormer base before commercial use. It is popular for virtual try-on and fashion tools, with more than 500 likes.
SegFormer model fine-tuned on ATR dataset for clothes segmentation but can also be used for human segmentation. The dataset on hugging face is called "mattmdjaga/humanparsingdataset". Labels: 0: "Background", 1: "Hat", 2: "Hair", 3: "Sunglasses", 4: "Upper-clothes", 5: "Skirt", 6: "Pants", 7: "Dress", 8: "Belt", 9: "Left-shoe", 10: "Right-shoe", 11: "Face", 12: "Left-leg", 13: "Right-leg", 14: "Left-arm", 15: "Right-arm", 16: "Bag", 17: "Scarf" The license for this model can be found here.
Excerpt from the card by Mateusz Dziemian, licensed other.
17 files, 548.5 MB in total. The weights are 7 files totalling 548.2 MB in bin, onnx, pt, pth, safetensors.
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 109.5 MB | 8f86fd90c567 |
| onnx/model.onnx | Weights | 110.0 MB | a93a8dac171b |
| optimizer.pt | Weights | 219.1 MB | 4f642f5c29cb |
| pytorch_model.bin | Weights | 109.6 MB | 934543143c97 |
| rng_state.pth | Weights | 14.6 KB | a7c38376dfee |
| scheduler.pt | Weights | 627 B | 7a9a297dec0f |
| training_args.bin | Weights | 3.3 KB | 210f58c34439 |
| config.json | Configuration | 1.7 KB | — |
| handler.py | Configuration | 1.5 KB | — |
| mattmdjaga_segformer_b2_clothes.json | Configuration | 4.9 KB | — |
| onnx/config.json | Configuration | 1.7 KB | — |
| onnx/preprocessor_config.json | Configuration | 431 B | — |
| preprocessor_config.json | Configuration | 271 B | — |
| trainer_state.json | Configuration | 291.3 KB | — |
| README.md | Documentation | 4.4 KB | — |
| .gitattributes | Repository | 1.5 KB | — |
| .gitignore | Repository | 29 B | — |
Released by Mateusz Dziemian through its official repository on Hugging Face.
| Precision | Weights in memory |
|---|---|
| As published | 548.2 MB |
| 16-bit | 0.1 GB |
| 8-bit | 0.0 GB |
| 4-bit | 0.0 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
About 0.1 GB at 16-bit and 0 GB at 4-bit: the weights (27M parameters) plus a working margin. A long context needs more.
At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
other, as its publisher declares it. Read the license text before commercial use.
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