Initial commit

Co-authored-by: Tim Dockhorn <timudk@users.noreply.huggingface.co>

.gitattributes

@@ -0,0 +1,35 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,39 @@
+---
+license: mit
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+inference: false
+---
+# SDXL - VAE
+
+#### How to use with 🧨 diffusers
+You can integrate this fine-tuned VAE decoder to your existing `diffusers` workflows, by including a `vae` argument to the `StableDiffusionPipeline`
+```py
+from diffusers.models import AutoencoderKL
+from diffusers import StableDiffusionPipeline
+
+model = "stabilityai/your-stable-diffusion-model"
+vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae")
+pipe = StableDiffusionPipeline.from_pretrained(model, vae=vae)
+```
+
+## Model 
+[SDXL](https://huggingface.co/stabilityai/stable-diffusion-xl-base-0.9) is a [latent diffusion model](https://arxiv.org/abs/2112.10752), where the diffusion operates in a pretrained, 
+learned (and fixed) latent space of an autoencoder. 
+While the bulk of the semantic composition is done by the latent diffusion model, 
+we can improve _local_, high-frequency details in generated images by improving the quality of the autoencoder. 
+To this end, we train the same autoencoder architecture used for the original [Stable Diffusion](https://github.com/CompVis/stable-diffusion) at a larger batch-size (256 vs 9) 
+and additionally track the weights with an exponential moving average (EMA). 
+The resulting autoencoder outperforms the original model in all evaluated reconstruction metrics, see the table below.
+
+
+## Evaluation 
+_SDXL-VAE vs original kl-f8 VAE vs f8-ft-MSE_
+### COCO 2017 (256x256, val, 5000 images)
+| Model    | rFID | PSNR         | SSIM          | PSIM          | Link                                                                                                 | Comments                                                                                        
+|----------|------|--------------|---------------|---------------|------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------|
+|          |      |              |               |               |                                                                                                      |                                                                                                 |
+| SDXL-VAE | 4.42 | 24.7 +/- 3.9 | 0.73 +/- 0.13 | 0.88 +/- 0.27 | https://huggingface.co/stabilityai/sdxl-vae/blob/main/sdxl_vae.safetensors                                                                                                     | as used in SDXL                                                                                 |
+| original | 4.99 | 23.4 +/- 3.8 | 0.69 +/- 0.14 | 1.01 +/- 0.28 | https://ommer-lab.com/files/latent-diffusion/kl-f8.zip                                               | as used in SD                                                                                   |
+| ft-MSE   | 4.70 | 24.5 +/- 3.7 | 0.71 +/- 0.13 | 0.92 +/- 0.27 | https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt | resumed with EMA from ft-EMA, emphasis on MSE (rec. loss = MSE + 0.1 * LPIPS), smoother outputs |

sdxl_vae.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:63aeecb90ff7bc1c115395962d3e803571385b61938377bc7089b36e81e92e2e
+size 334641164