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https://github.com/replicate/cog-sdxl

Stable Diffusion XL training and inference as a cog model
https://github.com/replicate/cog-sdxl

Last synced: 9 months ago
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Stable Diffusion XL training and inference as a cog model

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# Cog-SDXL

[![Replicate demo and cloud API](https://replicate.com/stability-ai/sdxl/badge)](https://replicate.com/stability-ai/sdxl)

This is an implementation of Stability AI's [SDXL](https://github.com/Stability-AI/generative-models) as a [Cog](https://github.com/replicate/cog) model.

## Development

Follow the [model pushing guide](https://replicate.com/docs/guides/push-a-model) to push your own fork of SDXL to [Replicate](https://replicate.com).

## Basic Usage

for prediction,

```bash
cog predict -i prompt="a photo of TOK"
```

```bash
cog train -i input_images=@example_datasets/__data.zip -i use_face_detection_instead=True
```

```bash
cog run -p 5000 python -m cog.server.http
```

## Update notes

**2023-08-17**
* ROI problem is fixed.
* Now BLIP caption_prefix does not interfere with BLIP captioner.

**2023-08-12**
* Input types are inferred from input name extensions, or from the `input_images_filetype` argument
* Preprocssing are now done with fp16, and if no mask is found, the model will use the whole image

**2023-08-11**
* Default to 768x768 resolution training
* Rank as argument now, default to 32
* Now uses Swin2SR `caidas/swin2SR-realworld-sr-x4-64-bsrgan-psnr` as default, and will upscale + downscale to 768x768