Update app.py

app.py

@@ -2,26 +2,26 @@ import gradio as gr
 import numpy as np
 import random
 
-# import spaces #[uncomment to use ZeroGPU]
-from diffusers import DiffusionPipeline
+import spaces
+from diffusers import AutoPipelineForText2Image
 import torch
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
 
 if torch.cuda.is_available():
     torch_dtype = torch.float16
 else:
     torch_dtype = torch.float32
 
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
+pipe = AutoPipelineForText2Image.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
+pipe.load_lora_weights('enhanceaiteam/Flux-uncensored', weight_name='lora.safetensors')
 pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
 
-# @spaces.GPU #[uncomment to use ZeroGPU]
+@spaces.GPU
 def infer(
     prompt,
     negative_prompt,
@@ -105,7 +105,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=1024,  
                 )
 
                 height = gr.Slider(
@@ -113,7 +113,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=1024,  
                 )
 
             with gr.Row():
@@ -122,7 +122,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=0.0,
                     maximum=10.0,
                     step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
+                    value=3.5,  
                 )
 
                 num_inference_steps = gr.Slider(
@@ -130,7 +130,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=2,  # Replace with defaults that work for your model
+                    value=28,  
                 )
 
         gr.Examples(examples=examples, inputs=[prompt])