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---
license: mit
tags:
- image-to-image
datasets:
- fka/awesome-chatgpt-prompts
language:
- ab
metrics:
- accuracy
base_model:
- stabilityai/stable-diffusion-3.5-large
new_version: microsoft/OmniParser
pipeline_tag: translation
library_name: adapter-transformers
---
## Notes
* This model is a trained version of the Keras Tutorial [Image Super Resolution](https://keras.io/examples/vision/super_resolution_sub_pixel/)
* The model has been trained on inputs of dimension 100x100 and outputs images of 300x300.
[Link to a pyimagesearch](https://www.pyimagesearch.com/2021/09/27/pixel-shuffle-super-resolution-with-tensorflow-keras-and-deep-learning/) tutorial I worked on, where we have used Residual blocks along with the Efficient sub pixel net. |