Update README.md

README.md

@@ -4,7 +4,7 @@ pipeline_tag: text-to-image
 
 # SDXS Onnx
 
-Converted from `SDXS-512-v0.9` (i.e. the original one, without dreamshaper) through this command:
+Converted from [IDKiro/sdxs-512-0.9](https://huggingface.co/IDKiro/sdxs-512-0.9) (i.e. the original one, without dreamshaper) through this command:
 
 ```
 optimum-cli export onnx -m <local absolute path to original model> --task stable-diffusion ./mysdxs
@@ -26,4 +26,31 @@ image = pipeline(prompt, num_inference_steps=1, guidance_scale=0).images[0]
 image.save("hello.png", "PNG")
 ```
 
-(TODO: write sample code for using TAESD)
+## Using with TAESD
+
+(Not tested yet)
+
+Consider using the Onnx converted model of TAESD at [deinferno/taesd-onnx](https://huggingface.co/deinferno/taesd-onnx) (Original model at [madebyollin/taesd](https://huggingface.co/madebyollin/taesd) )
+
+Combined inference code:
+
+```py
+from huggingface_hub import snapshot_download
+from diffusers.pipelines import OnnxRuntimeModel
+from optimum.onnxruntime import ORTStableDiffusionPipeline
+
+taesd_dir = snapshot_download(repo_id="deinferno/taesd-onnx")
+
+pipeline = ORTStableDiffusionPipeline.from_pretrained(
+      "lemonteaa/sdxs-onnx",
+      vae_decoder_session = OnnxRuntimeModel.from_pretrained(f"{taesd_dir}/vae_decoder"),
+      vae_encoder_session = OnnxRuntimeModel.from_pretrained(f"{taesd_dir}/vae_encoder"),
+      revision="onnx")
+
+prompt = "Sailing ship in storm by Leonardo da Vinci"
+
+image = pipeline(prompt, num_inference_steps=1, guidance_scale=0).images[0]
+
+image.save("hello.png", "PNG")
+```
+