test

app.py

@@ -12,7 +12,7 @@ def generate_image(prompt, num_inference_steps, guidance_scale):
     model_id = "stabilityai/stable-diffusion-xl-base-1.0"
     adapter_id = "latent-consistency/lcm-lora-sdxl"
 
-    pipe = AutoPipelineForText2Image.from_pretrained(model_id, torch_dtype=torch.float16, variant="fp16")
+    pipe = AutoPipelineForText2Image.from_pretrained(model_id, torch_dtype=torch.float32, variant="fp16")
     pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
     pipe.to("cuda")
 
@@ -28,7 +28,7 @@ def generate_image(prompt, num_inference_steps, guidance_scale):
 def inpaint_image(prompt, init_image, mask_image, num_inference_steps, guidance_scale):
     pipe = AutoPipelineForInpainting.from_pretrained(
         "diffusers/stable-diffusion-xl-1.0-inpainting-0.1",
-        torch_dtype=torch.float16,
+        torch_dtype=torch.float32,
         variant="fp16",
     ).to("cuda")
     pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
@@ -64,7 +64,7 @@ def generate_image_with_adapter(prompt, num_inference_steps, guidance_scale):
     pipe = DiffusionPipeline.from_pretrained(
     "stabilityai/stable-diffusion-xl-base-1.0",
     variant="fp16",
-    torch_dtype=torch.float16
+    torch_dtype=torch.float32
     ).to("cuda")
 
     # set scheduler
@@ -94,6 +94,10 @@ def modify_image(image, brightness, contrast):
     return image
 
 with gr.Blocks(gr.themes.Soft()) as demo:
+    with gr.Row():
+        gr.Markdown("## Latent Consistency for Diffusion Models")
+        gr.Markdown("Run this demo on your own machine if you would like: docker run -it -p 7860:7860 --platform=linux/amd64 --gpus all \
+	registry.hf.space/macadeliccc-lcm-papercut-demo:latest python app.py")
     with gr.Row():
         image_output = gr.Image(label="Generated Image")