Duplicate from caidas/swin2SR-classical-sr-x2-64

Co-authored-by: Niels Rogge <[email protected]>

.gitattributes

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README.md

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+---
+license: apache-2.0
+tags:
+- vision
+- image-to-image
+inference: false
+---
+
+# Swin2SR model (image super-resolution)
+
+Swin2SR model that upscales images x2. It was introduced in the paper [Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration](https://arxiv.org/abs/2209.11345)
+by Conde et al. and first released in [this repository](https://github.com/mv-lab/swin2sr). 
+
+# Intended use cases
+
+This model is intended for image super resolution.
+
+# Usage
+
+Refer to the [documentation](https://huggingface.co/docs/transformers/main/en/model_doc/swin2sr#transformers.Swin2SRForImageSuperResolution.forward.example).

config.json

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+{
+  "architectures": [
+    "Swin2SRForImageSuperResolution"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    6,
+    6,
+    6,
+    6,
+    6,
+    6
+  ],
+  "drop_path_rate": 0.1,
+  "embed_dim": 180,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "image_size": 64,
+  "img_range": 1.0,
+  "initializer_range": 0.02,
+  "layer_norm_eps": 1e-05,
+  "mlp_ratio": 2.0,
+  "model_type": "swin2sr",
+  "num_channels": 3,
+  "num_heads": [
+    6,
+    6,
+    6,
+    6,
+    6,
+    6
+  ],
+  "num_layers": 6,
+  "patch_size": 1,
+  "path_norm": true,
+  "qkv_bias": true,
+  "resi_connection": "1conv",
+  "torch_dtype": "float32",
+  "transformers_version": "4.26.0.dev0",
+  "upsampler": "pixelshuffle",
+  "upscale": 2,
+  "use_absolute_embeddings": false,
+  "window_size": 8
+}

preprocessor_config.json

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+{
+  "do_pad": true,
+  "do_rescale": true,
+  "image_processor_type": "Swin2SRImageProcessor",
+  "pad_size": 8,
+  "rescale_factor": 0.00392156862745098
+}

pytorch_model.bin

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