add more

app.py

@@ -114,6 +114,39 @@ 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",
+        use_safetensors=True,
+        add_watermarker=False,
+        variant="fp16",
+    )
+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",
+        use_safetensors=True,
+        add_watermarker=False,
+        variant="fp16",
+    )
+J7_pipe.to("cuda")
+
+j_pipe = StableDiffusionXLPipeline.from_pretrained(
+        "RunDiffusion/Juggernaut-XL",
+        vae=vae,
+        torch_dtype=torch.float16,
+        custom_pipeline="lpw_stable_diffusion_xl",
+        use_safetensors=True,
+        add_watermarker=False,
+        variant="fp16",
+    )
+J_pipe.to("cuda")
+
 @spaces.GPU
 def run_comparison(prompt: str,
     negative_prompt: str = "",
@@ -168,6 +201,43 @@ def run_comparison(prompt: str,
         output_type="pil",
     ).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
 
 examples = ["A dignified beaver wearing glasses, a vest, and colorful neck tie.",
@@ -259,8 +329,17 @@ with gr.Blocks(theme=gr.themes.Base()) as demo:
             gr.Markdown("## [Juggernaut-XL-10](https://huggingface.co)")
         with gr.Column():
             image_r5 = gr.Gallery(label="Juggernaut-XL-9",columns=1, preview=True,)
-            gr.Markdown("## [Juggernaut-XL-9](https://huggingface.co)")    
-    image_outputs = [image_r3, image_r4, image_r5]
+            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]
     gr.on(
         triggers=[prompt.submit, run.click],
         fn=run_comparison,