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commit files to HF hub

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README.md ADDED
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+ ---
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+ tags:
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+ - image-classification
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+ - pytorch
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+ - huggingpics
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+ metrics:
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+ - accuracy
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+
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+ model-index:
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+ - name: CartoonOrNotv2
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9836065769195557
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+ ---
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+
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+ # CartoonOrNotv2
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+
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+
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+ CartoonOrNot Model using Swin Transformer Architecture
config.json ADDED
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+ {
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+ "_name_or_path": "umm-maybe/AI-image-detector",
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+ "architectures": [
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+ "SwinForImageClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "depths": [
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+ "drop_path_rate": 0.1,
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+ "embed_dim": 128,
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+ "encoder_stride": 32,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 1024,
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+ "id2label": {
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+ "0": "cartoon",
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+ "1": "not_cartoon"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "label2id": {
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+ "cartoon": "0",
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+ "not_cartoon": "1"
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+ },
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+ "layer_norm_eps": 1e-05,
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+ "max_length": 128,
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+ "mlp_ratio": 4.0,
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+ "model_type": "swin",
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+ "num_channels": 3,
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+ "num_layers": 4,
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+ "padding": "max_length",
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+ "patch_size": 4,
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+ "path_norm": true,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "stage_names": [
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+ "stem",
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+ "stage1",
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+ "stage2",
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+ "stage3",
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+ "stage4"
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+ ],
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.2",
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+ "use_absolute_embeddings": false,
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+ "window_size": 7
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+ }
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preprocessor_config.json ADDED
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