mask2former-swin-tiny-cityscapes-panoptic
facebook/mask2former-swin-tiny-cityscapes-panoptic
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 9,766
- Total downloadsCumulative all-time download counter reported by the source platform.
- 41.7K
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
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- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 0
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #60 among tracked Image Segmentation models.
- #7,868
- –this week
- Parameters
- 47.4M
- Last source update
- Sep 11, 2023
Downloads over time
Daily gain between consecutive observationsNot enough tracked history yet for a chart.
OpenModelStats began tracking this model on 2026-08-24. Charts appear as daily observations accumulate.
Likes over time
Not enough tracked history yet for a chart.
OpenModelStats began tracking this model on 2026-08-24. Charts appear as daily observations accumulate.
Rank among tracked models
Lower is betterNot enough tracked history yet for a chart.
OpenModelStats began tracking this model on 2026-08-24. Charts appear as daily observations accumulate.
Overview
mask2former-swin-tiny-cityscapes-panoptic is a image segmentation model published by facebook. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 8h ago.
- Published
- Jan 3, 2023
- Last updated
- Sep 11, 2023
- Library
- transformers
- License
- other
- Task
- Image Segmentation
- Parameters
- 47,434,798
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- —
transformerspytorchsafetensorsmask2formervisionimage-segmentationdataset:cocoarxiv:2112.01527arxiv:2107.06278license:otherendpoints_compatibleregion:us
Publisher
facebookView publisher statistics →Similar models
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