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distillBEiT

Image Classification
Transformers
PyTorch
mobilenet_v2
Inference Endpoints
Model card Files Community
distillBEiT
File size: 1,481 Bytes 
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{
  "architectures": [
    "MobileNetV2ForImageClassification"
  ],
  "classifier_dropout_prob": 0.8,
  "depth_divisible_by": 8,
  "depth_multiplier": 1.0,
  "expand_ratio": 6,
  "finegrained_output": true,
  "first_layer_is_expansion": true,
  "hidden_act": "relu6",
  "id2label": {
    "0": "document_edf",
    "1": "facture_amazon",
    "2": "facture_edenkia",
    "3": "facture_edf",
    "4": "facture_engie",
    "5": "facture_mint",
    "6": "facture_misc",
    "7": "facture_orange",
    "8": "facture_primagaz",
    "9": "facture_primeo",
    "10": "facture_sicap",
    "11": "facture_smeg",
    "12": "facture_sosh",
    "13": "facture_totalenergies",
    "14": "ticket_carburant",
    "15": "ticket_misc",
    "16": "ticket_restaurant",
    "17": "ticket_store"
  },
  "image_size": 224,
  "initializer_range": 0.02,
  "label2id": {
    "LABEL_0": 0,
    "LABEL_1": 1,
    "LABEL_10": 10,
    "LABEL_11": 11,
    "LABEL_12": 12,
    "LABEL_13": 13,
    "LABEL_14": 14,
    "LABEL_15": 15,
    "LABEL_16": 16,
    "LABEL_17": 17,
    "LABEL_2": 2,
    "LABEL_3": 3,
    "LABEL_4": 4,
    "LABEL_5": 5,
    "LABEL_6": 6,
    "LABEL_7": 7,
    "LABEL_8": 8,
    "LABEL_9": 9
  },
  "layer_norm_eps": 0.001,
  "min_depth": 8,
  "model_type": "mobilenet_v2",
  "num_channels": 3,
  "output_stride": 32,
  "problem_type": "single_label_classification",
  "semantic_loss_ignore_index": 255,
  "tf_padding": true,
  "torch_dtype": "float32",
  "transformers_version": "4.33.1"
}