Update app.py

app.py

@@ -114,29 +114,7 @@ J9_pipe = StableDiffusionXLPipeline.from_pretrained(
     )
 J9_pipe.to("cuda")
 
-J8_pipe = StableDiffusionXLPipeline.from_pretrained(
-        "RunDiffusion/Juggernaut-XL-v8",
-        vae=vae,
-        torch_dtype=torch.float16,
-        custom_pipeline="lpw_stable_diffusion_xl",
-    )
-J8_pipe.to("cuda")
 
-J7_pipe = StableDiffusionXLPipeline.from_pretrained(
-        "RunDiffusion/Juggernaut-XL-v7",
-        vae=vae,
-        torch_dtype=torch.float16,
-        custom_pipeline="lpw_stable_diffusion_xl",
-    )
-J7_pipe.to("cuda")
-
-J_pipe = StableDiffusionXLPipeline.from_pretrained(
-        "RunDiffusion/Juggernaut-XL",
-        vae=vae,
-        torch_dtype=torch.float16,
-        custom_pipeline="lpw_stable_diffusion_xl",
-    )
-J_pipe.to("cuda")
 
 @spaces.GPU
 def run_comparison(prompt: str,
@@ -193,41 +171,6 @@ def run_comparison(prompt: str,
     ).images
     image_paths_r5 = [save_image(img) for img in image_r5]
 
-    image_r6 = J8_pipe(prompt=prompt,
-        negative_prompt=negative_prompt,
-        width=width,
-        height=height,
-        guidance_scale=guidance_scale,
-        num_inference_steps=num_inference_steps,
-        num_images_per_prompt=num_images_per_prompt,
-        cross_attention_kwargs={"scale": 0.65},
-        output_type="pil",
-    ).images
-    image_paths_r6 = [save_image(img) for img in image_r6]
-
-    image_r7 = J7_pipe(prompt=prompt,
-        negative_prompt=negative_prompt,
-        width=width,
-        height=height,
-        guidance_scale=guidance_scale,
-        num_inference_steps=num_inference_steps,
-        num_images_per_prompt=num_images_per_prompt,
-        cross_attention_kwargs={"scale": 0.65},
-        output_type="pil",
-    ).images
-    image_paths_r7 = [save_image(img) for img in image_r7]
-
-    image_r8 = J_pipe(prompt=prompt,
-        negative_prompt=negative_prompt,
-        width=width,
-        height=height,
-        guidance_scale=guidance_scale,
-        num_inference_steps=num_inference_steps,
-        num_images_per_prompt=num_images_per_prompt,
-        cross_attention_kwargs={"scale": 0.65},
-        output_type="pil",
-    ).images
-    image_paths_r8 = [save_image(img) for img in image_r8]
     
     return image_paths_r3, image_paths_r4,image_paths_r5, seed
 
@@ -321,16 +264,7 @@ with gr.Blocks(theme=gr.themes.Base()) as demo:
         with gr.Column():
             image_r5 = gr.Gallery(label="Juggernaut-XL-9",columns=1, preview=True,)
             gr.Markdown("## [Juggernaut-XL-9](https://huggingface.co)") 
-        with gr.Column():
-            image_r6 = gr.Gallery(label="Juggernaut-XL-8",columns=1, preview=True,)
-            gr.Markdown("## [Juggernaut-XL-8](https://huggingface.co)")
-        with gr.Column():
-            image_r7 = gr.Gallery(label="Juggernaut-XL-7",columns=1, preview=True,)
-            gr.Markdown("## [Juggernaut-XL-7](https://huggingface.co)")
-        with gr.Column():
-            image_r8 = gr.Gallery(label="Juggernaut-XL",columns=1, preview=True,)
-            gr.Markdown("## [Juggernaut-XL](https://huggingface.co)")
-    image_outputs = [image_r3, image_r4, image_r5, image_r6, image_r7, image_r8]
+    image_outputs = [image_r3, image_r4, image_r5]
     gr.on(
         triggers=[prompt.submit, run.click],
         fn=run_comparison,