{
  "mic": "0.3",
  "name": "OWLv2 open-vocabulary object detection",
  "usage": "Owlv2Processor + Owlv2ForObjectDetection, two synthetic images, two text queries, post-processing, and one SGD step on detection labels",
  "architecture": "Owlv2ForObjectDetection",
  "checkpoints": {
    "google/owlv2-base-patch16-ensemble": {
      "fixture": "huggingface-mic/owlv2-base-patch16-ensemble-mic"
    }
  },
  "fixtures": {
    "huggingface-mic/owlv2-base-patch16-ensemble-mic": {
      "built_from": "google/owlv2-base-patch16-ensemble",
      "covers": [
        "google/owlv2-base-patch16-ensemble"
      ],
      "build": {
        "seed": 17,
        "model_class": "Owlv2ForObjectDetection",
        "accept_insensitive": {
          "attention_mask:all_ones": "OWLv2's text tower is causal and pools at the EOS token, so padding after EOS cannot move any output"
        }
      }
    }
  },
  "integrations": {
    "transformers": {
      "entry_point": "integrations/transformers/usage.md",
      "format": "runnable-markdown",
      "requires": [
        "transformers>=5",
        "torch",
        "torchvision"
      ],
      "targets": [
        "fixtures",
        "checkpoints"
      ],
      "variants": {
        "default": {},
        "bfloat16": {
          "dtype": "bfloat16"
        }
      },
      "training": true,
      "resources": {
        "fixture": {
          "memory_gb": 4,
          "download_mb": 50
        },
        "google/owlv2-base-patch16-ensemble": {
          "memory_gb": 8,
          "gpu_memory_gb": 8,
          "download_mb": 1200,
          "variants": {
            "bfloat16": {
              "gpu_memory_gb": 6
            }
          }
        }
      }
    }
  },
  "outputs": {
    "runtime": {
      "compare": "exact"
    },
    "detections": {
      "compare": "exact"
    },
    "logits_probe": {
      "compare": "allclose",
      "atol": 0.0001,
      "rtol": 0.0001
    },
    "boxes_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"
    }
  }
}