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custom-resnet

Image Classification
Transformers
PyTorch
resnet
Inference Endpoints
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custom-resnet
File size: 1,138 Bytes 
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{
  "_name_or_path": "microsoft/resnet-50",
  "architectures": [
    "ResNetForImageClassification"
  ],
  "depths": [
    3,
    4,
    6,
    3
  ],
  "downsample_in_first_stage": false,
  "embedding_size": 64,
  "hidden_act": "relu",
  "hidden_sizes": [
    256,
    512,
    1024,
    2048
  ],
  "id2label": {
    "0": " Renaissance",
    "1": " Surrealism",
    "10": " romanticism",
    "2": " Unlabeled",
    "3": " baroque",
    "4": " cubism",
    "5": " cubsim",
    "6": " minimalist",
    "7": " popart",
    "8": " realism",
    "9": " renaissance"
  },
  "label2id": {
    " Renaissance": "0",
    " Surrealism": "1",
    " Unlabeled": "2",
    " baroque": "3",
    " cubism": "4",
    " cubsim": "5",
    " minimalist": "6",
    " popart": "7",
    " realism": "8",
    " renaissance": "9",
    " romanticism": "10"
  },
  "layer_type": "bottleneck",
  "model_type": "resnet",
  "num_channels": 3,
  "out_features": [
    "stage4"
  ],
  "out_indices": [
    4
  ],
  "stage_names": [
    "stem",
    "stage1",
    "stage2",
    "stage3",
    "stage4"
  ],
  "torch_dtype": "float32",
  "transformers_version": "4.31.0"
}