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mask2former-swin-tiny-coco-instance-mic

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mask2former-swin-tiny-coco-instance-mic
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{
  "mic": "0.3",
  "name": "Mask2Former instance segmentation",
  "usage": "AutoImageProcessor + Mask2FormerForUniversalSegmentation, batched synthetic images, instance-segmentation labels, one SGD step",
  "architecture": "Mask2FormerForUniversalSegmentation",
  "checkpoints": {
    "facebook/mask2former-swin-tiny-coco-instance": {
      "fixture": "huggingface-mic/mask2former-swin-tiny-coco-instance-mic"
    }
  },
  "fixtures": {
    "huggingface-mic/mask2former-swin-tiny-coco-instance-mic": {
      "built_from": "facebook/mask2former-swin-tiny-coco-instance",
      "covers": [
        "facebook/mask2former-swin-tiny-coco-instance"
      ],
      "build": {
        "seed": 17,
        "model_class": "Mask2FormerForUniversalSegmentation"
      }
    }
  },
  "integrations": {
    "transformers": {
      "entry_point": "integrations/transformers/usage.md",
      "format": "runnable-markdown",
      "requires": [
        "transformers>=5",
        "torch"
      ],
      "targets": [
        "fixtures",
        "checkpoints"
      ],
      "variants": {
        "default": {},
        "eager": {
          "attn_implementation": "eager"
        },
        "bfloat16": {
          "dtype": "bfloat16"
        }
      },
      "training": true,
      "resources": {
        "fixture": {
          "memory_gb": 4,
          "download_mb": 200
        },
        "facebook/mask2former-swin-tiny-coco-instance": {
          "memory_gb": 8,
          "gpu_memory_gb": 8,
          "download_mb": 200,
          "variants": {
            "bfloat16": {
              "gpu_memory_gb": 6
            }
          }
        }
      }
    }
  },
  "outputs": {
    "runtime": {
      "compare": "exact"
    },
    "class_logits_probe": {
      "compare": "allclose",
      "atol": 0.0001,
      "rtol": 0.0001
    },
    "mask_logits_probe": {
      "compare": "allclose",
      "atol": 0.0001,
      "rtol": 0.0001
    },
    "training.loss": {
      "compare": "allclose",
      "atol": 0.0001,
      "rtol": 0.0001
    },
    "training.gradients": {
      "compare": "all_true"
    },
    "training.updated": {
      "compare": "true"
    }
  }
}