Update README.md

README.md

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-license: cc-by-4.0
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+---
+license: cc-by-4.0
+pipeline_tag: image-to-image
+tags:
+- pytorch
+- super-resolution
+---
+
+[Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xNomos8kHAT-L_bokeh_jpg)  
+
+# 4xNomos8kHAT-L_bokeh_jpg
+
+Name: 4xNomos8kHAT-L_bokeh_jpg  
+Author: Philip Hofmann  
+Release: 05.10.2023  
+License: CC BY 4.0  
+Network: HAT  
+Scale: 4  
+Purpose: 4x photo upscaler (handles bokeh effect and jpg compression)  
+Iterations: 145000  
+epoch: 66  
+batch_size: 4  
+HR_size: 128  
+Dataset: nomos8k  
+Number of train images: 8492  
+OTF Training: No  
+Pretrained_Model_G: HAT-L_SRx4_ImageNet-pretrain  
+
+Description:  
+4x photo upscaler, made to specifically handle bokeh effect and jpg compression. Basically a HAT-L variant of the already released 4xNomosUniDAT_bokeh_jpg model, but specifically trained for photos on the nomos8k dataset (and hopefully without the smoothing effect).
+
+The three strengths of this model (design purpose):  
+Specifically for photos / photography  
+Handles bokeh effect  
+Handles jpg compression  
+
+This model will not attempt to:  
+Denoise  
+Deblur