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AI 模型 84757

• PIT-4B-FT-202012↗

  Diamegs

• semsimula-ladder-live-owt-d384-l2-none-norc-sr2-fob↗

  dimitarpg13

• granite-4.1-3b-GGUF↗

  Dzluck

• sentence-transformers-multilingual-e5-base↗

  embaas

• Qwen3.8-27B-Escha-W2↗

  EschaLabs

• gemma-4-E4B-it-ultra-uncensored-heretic-GGUF↗

  eyentsign

• mask2former-swin-base-ade-semantic↗

  facebook

  Mask2Former model trained on ADE20k semantic segmentation (base-sized version, Swin backbone). It was introduced in the paper Masked-attention Mask Transformer for Universal Image Segmentation and first released in this repository. Disclaimer: The team releasing Mask2Former did not write a model card for this model so this model card has been written by the Hugging Face team. Mask2Former addresses instance, semantic and panoptic segmentation with the same paradigm: by predicting a set of masks and corresponding labels. Hence, all 3 tasks are treated as if they were instance segmentation. Mask2Former outperforms the previous SOTA, MaskFormer both in terms of performance an efficiency by (i) replacing the pixel decoder with a more advanced multi-scale deformable attention Transformer, (ii) adopting a Transformer decoder with masked attention to boost performance without without introducing additional computation and (iii) improving training efficiency by calculating the loss on subsampled points instead of whole masks.

• mms-tts-med↗

  facebook

• gemma-4-E2B-it-qat-q4_0-heretic-GGUF↗

  FadedRedStar

• Qwen3.8-27B-GGUF↗

  GalaxyS2Gordon