Upload tiny models for SwinForImageClassification

config.json

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+{
+  "_name_or_path": "tiny_models/swin/SwinForImageClassification",
+  "architectures": [
+    "SwinForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    1,
+    2,
+    1
+  ],
+  "drop_path_rate": 0.1,
+  "embed_dim": 16,
+  "encoder_stride": 8,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 64,
+  "image_size": 32,
+  "initializer_range": 0.02,
+  "layer_norm_eps": 1e-05,
+  "mlp_ratio": 2.0,
+  "model_type": "swin",
+  "num_channels": 3,
+  "num_heads": [
+    2,
+    2,
+    4
+  ],
+  "num_layers": 3,
+  "out_features": [
+    "stage1",
+    "stage2"
+  ],
+  "patch_size": 2,
+  "path_norm": true,
+  "qkv_bias": true,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.28.0.dev0",
+  "use_absolute_embeddings": false,
+  "window_size": 2
+}

preprocessor_config.json

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+{
+  "crop_size": 32,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 32,
+    "width": 32
+  }
+}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6e73c9bd31918450ca30bac9f5fd56c615038b393afd8d1eed487778d832e19d
+size 284723

tf_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f89a07fe10fdcd78e6aaecdbc23e61b6aff5527d9478766796e8e3ff6de74250
+size 378224