Hugging Face's logo

hf-internal-testing
/
mic-table_transformer-integration

mic
test-artifact
Model card Files
xet
 Community
mic-table_transformer-integration
File size: 1,850 Bytes
526a660
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
{
  "mic": "0.3",
  "name": "Table Transformer Detection",
  "usage": "AutoProcessor + AutoModelForObjectDetection, batched synthetic images, object detection with training step",
  "architecture": "TableTransformerForObjectDetection",
  "checkpoints": {
    "microsoft/table-transformer-detection": {
      "fixture": "hf-internal-testing/mic-table_transformer-slim"
    }
  },
  "fixtures": {
    "hf-internal-testing/mic-table_transformer-slim": {
      "built_from": "microsoft/table-transformer-detection",
      "covers": [
        "microsoft/table-transformer-detection"
      ],
      "build": {
        "seed": 17
      }
    }
  },
  "integrations": {
    "transformers": {
      "entry_point": "integrations/transformers/usage.md",
      "format": "runnable-markdown",
      "requires": [
        "transformers>=5",
        "torch"
      ],
      "targets": [
        "fixtures"
      ],
      "variants": {
        "default": {},
        "eager": {
          "attn_implementation": "eager"
        },
        "bfloat16": {
          "dtype": "bfloat16"
        }
      },
      "training": true,
      "resources": {
        "fixture": {
          "memory_gb": 1,
          "download_mb": 20
        },
        "microsoft/table-transformer-detection": {
          "memory_gb": 2,
          "download_mb": 150
        }
      }
    }
  },
  "outputs": {
    "runtime": {
      "compare": "exact"
    },
    "inference_scores": {
      "compare": "allclose",
      "atol": 0.0001,
      "rtol": 0.0001
    },
    "inference_boxes": {
      "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"
    }
  }
}