Update app.py

app.py

@@ -3,7 +3,7 @@ import torch
 import numpy as np
 import modin.pandas as pd
 from PIL import Image
-from diffusers import DiffusionPipeline #, StableDiffusion3Pipeline
+from diffusers import DiffusionPipeline, CogView4Pipeline #, StableDiffusion3Pipeline from diffusers import CogView4Pipeline
 from huggingface_hub import hf_hub_download
 
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
@@ -33,10 +33,18 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed):
         torch.cuda.empty_cache()
         return image
 
+    if Model == "Club":
+        pipe = CogView4Pipeline.from_pretrained("THUDM/CogView4-6B", torch_dtype=torch.bfloat16)
+        # Open it for reduce GPU memory usage
+        pipe.enable_model_cpu_offload()
+        pipe.vae.enable_slicing()
+        pipe.vae.enable_tiling()
+        image = pipe(prompt=Prompt, guidance_scale=scale, num_images_per_prompt=1, num_inference_steps=steps, width=1024, height=1024,).images[0]
+        return image
     
     return image
     
-gr.Interface(fn=genie, inputs=[gr.Radio(['PhotoReal', 'Animagine XL 4',], value='PhotoReal', label='Choose Model'),
+gr.Interface(fn=genie, inputs=[gr.Radio(['PhotoReal', 'Animagine XL 4', "Club"], value='PhotoReal', label='Choose Model'),
                                gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'), 
                                gr.Textbox(label='What you Do Not want the AI to generate. 77 Token Limit'),
                                gr.Slider(512, 1024, 768, step=128, label='Height'),