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owlvit-base-patch32-mic

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owlvit-base-patch32-mic
File size: 2,145 Bytes
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{
  "mic": "0.3",
  "name": "OWL-ViT open-vocabulary object detection",
  "usage": "OwlViTProcessor + OwlViTForObjectDetection, batched text queries and images, explicit detection loss for training",
  "architecture": "OwlViTForObjectDetection",
  "checkpoints": {
    "google/owlvit-base-patch32": {
      "fixture": "huggingface-mic/owlvit-base-patch32-mic"
    }
  },
  "fixtures": {
    "huggingface-mic/owlvit-base-patch32-mic": {
      "built_from": "google/owlvit-base-patch32",
      "covers": [
        "google/owlvit-base-patch32"
      ],
      "build": {
        "seed": 17,
        "model_class": "OwlViTForObjectDetection",
        "accept_insensitive": {
          "attention_mask:all_ones": "OWL-ViT'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": {},
        "eager": {
          "attn_implementation": "eager"
        },
        "bfloat16": {
          "dtype": "bfloat16"
        }
      },
      "training": true,
      "resources": {
        "fixture": {
          "memory_gb": 2,
          "download_mb": 20
        },
        "google/owlvit-base-patch32": {
          "memory_gb": 4,
          "download_mb": 620
        }
      }
    }
  },
  "outputs": {
    "runtime": {
      "compare": "exact"
    },
    "detections.boxes": {
      "compare": "allclose",
      "atol": 0.0001,
      "rtol": 0.0001
    },
    "detections.scores": {
      "compare": "allclose",
      "atol": 0.0001,
      "rtol": 0.0001
    },
    "detections.labels": {
      "compare": "exact"
    },
    "training.loss": {
      "compare": "allclose",
      "atol": 0.0001,
      "rtol": 0.0001
    },
    "training.gradients": {
      "compare": "all_true"
    },
    "training.updated": {
      "compare": "true"
    }
  }
}