merge

README.md

@@ -5,13 +5,14 @@ tags:
 - stable-diffusion-diffusers
 inference: false
 ---
-# Watermarked Autoencoder (weak watermark)
 
-## Utilizing
-These weights are intended to be used with the [🧨 diffusers library](https://github.com/huggingface/diffusers).
+# Watermarked (weak) VAE for SDXL
+
+You can use this watermarked VAE for your existing SDXL image generation pipelines 
+to make sure generated images are watermarked.
+
+## Usage
 
-#### How to use with 🧨 diffusers
-You can integrate this watermarked VAE decoder to your existing `diffusers` workflows, by including a `vae` argument to the `StableDiffusionPipeline`
 ```py
 from diffusers.models import AutoencoderKL
 from diffusers import StableDiffusionXLPipeline
@@ -21,12 +22,10 @@ model = "stabilityai/sdxl-turbo"
 vae = AutoencoderKL.from_pretrained("imatag/stable-signature-bzh-sdxl-vae-weak")
 
 pipe = StableDiffusionXLPipeline.from_pretrained(model, vae=vae)
-image = pipe("a photo of an astronaut riding a horse on mars",
-             num_inference_steps=4,
-             guidance_scale=0.0,
-             output_type="pil").images[0]
 ```
 
+For more information, please have a look at [the official demo](https://huggingface.co/spaces/imatag/stable-signature-bzh)
+
 ## Decoder Finetuning
 
 This model was finetuned from the original StableDiffusion-XL autoencoder with the additional objective of including a weak invisible watermark, following the procedure of [StableSignature](https://ai.meta.com/blog/stable-signature-watermarking-generative-ai/). This watermark is detectable by [IMATAG](https://www.imatag.com/)'s demo BZH decoder, available via API.
@@ -87,4 +86,4 @@ The Receiver Operating Characteristic curve shows its performance under no modif
 </p>
 
 More details available in our [announcement](https://www.imatag.com/blog/unlocking-the-future-of-content-authentication-imatags-breakthrough-in-ai-generated-image-watermarking) and our lab's [blog post](https://imatag-lab.medium.com/stable-signature-meets-bzh-53ad0ba13691).
-For watermarked models with a different key, other perceptual compromises, robustness to other attacks, or faster detection, please [contact IMATAG](https://pages.imatag.com/contact-us-imatag).
+For watermarked models with a different key, support for payload, other perceptual compromises, robustness to other attacks, or faster detection, please [contact IMATAG](https://pages.imatag.com/contact-us-imatag).