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Text2Image_PyData_23

Image Classification
Transformers
PyTorch
swin
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Text2Image_PyData_23
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{
  "_name_or_path": "juliensimon/autotrain-chest-xray-demo-1677859324",
  "architectures": [
    "SwinForImageClassification"
  ],
  "attention_probs_dropout_prob": 0.0,
  "depths": [
    2,
    2,
    18,
    2
  ],
  "drop_path_rate": 0.1,
  "embed_dim": 128,
  "encoder_stride": 32,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.0,
  "hidden_size": 1024,
  "id2label": {
    "0": "NORMAL",
    "1": "PNEUMONIA"
  },
  "image_size": 224,
  "initializer_range": 0.02,
  "label2id": {
    "NORMAL": "0",
    "PNEUMONIA": "1"
  },
  "layer_norm_eps": 1e-05,
  "max_length": 128,
  "mlp_ratio": 4.0,
  "model_type": "swin",
  "num_channels": 3,
  "num_heads": [
    4,
    8,
    16,
    32
  ],
  "num_layers": 4,
  "out_features": [
    "stage4"
  ],
  "out_indices": [
    4
  ],
  "padding": "max_length",
  "patch_size": 4,
  "path_norm": true,
  "problem_type": "single_label_classification",
  "qkv_bias": true,
  "stage_names": [
    "stem",
    "stage1",
    "stage2",
    "stage3",
    "stage4"
  ],
  "torch_dtype": "float32",
  "transformers_version": "4.34.1",
  "use_absolute_embeddings": false,
  "window_size": 7
}