add requirements

app.py

@@ -2,16 +2,16 @@ import gradio as gr
 import numpy as np
 import random
 
-import spaces #[uncomment to use ZeroGPU]
+import spaces  # [uncomment to use ZeroGPU]
 from diffusers import DiffusionPipeline
 import torch
 
 
 model_ids = [
-    'Prgckwb/trpfrog-sd3.5-large',
-    'Prgckwb/trpfrog-sd3.5-medium',
-    'Prgckwb/trpfrog-sdxl',
-    'Prgckwb/trpfrog-diffusion',
+    "Prgckwb/trpfrog-sd3.5-large",
+    "Prgckwb/trpfrog-sd3.5-medium",
+    "Prgckwb/trpfrog-sdxl",
+    "Prgckwb/trpfrog-diffusion",
 ]
 
 if torch.cuda.is_available():
@@ -21,15 +21,21 @@ else:
     torch_dtype = torch.float32
     device = "cpu"
 
-pipelines = {model_id: DiffusionPipeline.from_pretrained(model_id, device=device, dtype=torch_dtype) for model_id in model_ids}
+pipelines = {
+    model_id: DiffusionPipeline.from_pretrained(
+        model_id, device=device, dtype=torch_dtype
+    )
+    for model_id in model_ids
+}
+
 
 @spaces.GPU()
 def inference(
-        model_id: str,
-        prompt: str,
-        width: int,
-        height: int,
-        progress=gr.Progress(track_tqdm=True),
+    model_id: str,
+    prompt: str,
+    width: int,
+    height: int,
+    progress=gr.Progress(track_tqdm=True),
 ):
     pipe = pipelines[model_id].to(device)
 
@@ -42,21 +48,20 @@ def inference(
     return image
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     theme = gr.themes.Ocean()
 
     demo = gr.Interface(
         fn=inference,
         inputs=[
-            gr.Dropdown(label='Model', choices=model_ids, value=model_ids[0]),
-            gr.Textbox(label='Prompt', placeholder='an icon of trpfrog'),
-            gr.Slider(label='Width', minimum=64, maximum=1024, step=64, value=1024),
-            gr.Slider(label='Height', minimum=64, maximum=1024, step=64, value=1024),
+            gr.Dropdown(label="Model", choices=model_ids, value=model_ids[0]),
+            gr.Textbox(label="Prompt", placeholder="an icon of trpfrog"),
+            gr.Slider(label="Width", minimum=64, maximum=1024, step=64, value=1024),
+            gr.Slider(label="Height", minimum=64, maximum=1024, step=64, value=1024),
         ],
         outputs=[
-            gr.Image(label='Output'),
+            gr.Image(label="Output"),
         ],
         theme=theme,
     )
     demo.queue().launch()
-

requirements.txt

@@ -1,3 +1,6 @@
 diffusers
 safetensors
 accelerate
+transformers
+sentencepiece
+protobuf