Add SD1.5 example to README.MD

README.md

@@ -20,6 +20,50 @@ on real images. Plus it is MIT licensed so you can do whatever you want with it.
 ### Compare
 Check out the comparison at [imgsli](https://imgsli.com/Mjc2MjA3).
 
+### Use with SD1.5 (Diffusers)
+```py
+import torch
+from diffusers import AutoencoderKL, StableDiffusionPipeline
+from huggingface_hub import hf_hub_download
+from safetensors.torch import load_file
+
+model_id = "runwayml/stable-diffusion-v1-5"
+decoder_id = "ostris/vae-kl-f8-d16"
+adapter_id = "ostris/16ch-VAE-Adapters"
+adapter_ckpt = "16ch-VAE-Adapter-SD15-alpha.safetensors"
+dtype = torch.float16
+
+vae = AutoencoderKL.from_pretrained(decoder_id, torch_dtype=dtype)
+pipe = StableDiffusionPipeline.from_pretrained(model_id, vae=vae, torch_dtype=torch.float16)
+
+ckpt_file = hf_hub_download(adapter_id, adapter_ckpt)
+ckpt = load_file(ckpt_file)
+
+lora_state_dict = {k: v for k, v in ckpt.items() if "lora" in k}
+unet_state_dict = {k.replace("unet_", ""): v for k, v in ckpt.items() if "unet_" in k}
+
+pipe.unet.conv_in = torch.nn.Conv2d(16, 320, 3, 1, 1)
+pipe.unet.conv_out = torch.nn.Conv2d(320, 16, 3, 1, 1)
+pipe.unet.load_state_dict(unet_state_dict, strict=False)
+pipe.unet.conv_in.to(dtype)
+pipe.unet.conv_out.to(dtype)
+pipe.unet.config.in_channels = 16
+pipe.unet.config.out_channels = 16
+
+pipe.load_lora_weights(lora_state_dict)
+pipe.fuse_lora()
+
+pipe = pipe.to("cuda")
+prompt = "a photo of an astronaut riding a horse on mars"
+negative_prompt = (
+    "ugly, tiling, poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame,"
+    "extra limbs, disfigured, deformed, body out of frame, bad anatomy, watermark, signature,"
+    "cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face"
+)
+image = pipe(prompt, negative_prompt=negative_prompt).images[0]
+
+image.save("astronaut_rides_horse.png")
+```
 
 ### What do I do with this?