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Upload tiny models for EfficientNetForImageClassification
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{
"architectures": [
"EfficientNetForImageClassification"
],
"batch_norm_eps": 0.001,
"batch_norm_momentum": 0.99,
"depth_coefficient": 3.1,
"depth_divisor": 8,
"depthwise_padding": [],
"drop_connect_rate": 0.2,
"dropout_rate": 0.5,
"expand_ratios": [
1,
6,
6
],
"hidden_act": "gelu",
"hidden_dim": 2560,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1",
"2": "LABEL_2",
"3": "LABEL_3",
"4": "LABEL_4",
"5": "LABEL_5",
"6": "LABEL_6",
"7": "LABEL_7",
"8": "LABEL_8",
"9": "LABEL_9"
},
"image_size": 600,
"in_channels": [
32,
16,
24
],
"initializer_range": 0.02,
"kernel_sizes": [
3,
3,
5
],
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1,
"LABEL_2": 2,
"LABEL_3": 3,
"LABEL_4": 4,
"LABEL_5": 5,
"LABEL_6": 6,
"LABEL_7": 7,
"LABEL_8": 8,
"LABEL_9": 9
},
"model_type": "efficientnet",
"num_block_repeats": [
1,
1,
2
],
"num_channels": 3,
"num_hidden_layers": 16,
"out_channels": [
16,
24,
40
],
"pooling_type": "mean",
"squeeze_expansion_ratio": 0.25,
"strides": [
1,
1,
2
],
"torch_dtype": "float32",
"transformers_version": "4.28.0.dev0",
"width_coefficient": 2.0
}