change params

app.py

@@ -29,8 +29,12 @@ pipe.controlnet.to(torch.bfloat16)
 
 MARKDOWN = """
 # FLUX.1-dev-Inpainting
+
+#### VERSION: 0.0.3_beta
+
 Original Model: Flux.1-dev
 FluxControlNet: alimama-creative
+
 """
 
 @spaces.GPU()
@@ -79,13 +83,14 @@ with gr.Blocks() as demo:
                 layers=False,
                 brush=gr.Brush(colors=["#FFFFFF"], color_mode="fixed"))
 
+
             prompt = gr.Textbox(lines=2, placeholder="Enter prompt here...")
             negative_prompt = gr.Textbox(lines=2, placeholder="Enter negative_prompt here...")
-            controlnet_conditioning_scale = gr.Slider(minimum=0, step=0.01, maximum=1, value=0.9, label="controlnet_conditioning_scale")
-            guidance_scale = gr.Slider(minimum=1, step=0.5, maximum=10, value=3.5, label="Image to generate")
+            controlnet_conditioning_scale = gr.Slider(minimum=0, step=0.01, maximum=1, value=0.8, label="controlnet_conditioning_scale")  # Adjusted value
+            guidance_scale = gr.Slider(minimum=1, step=0.5, maximum=10, value=5.0, label="Image to generate")  # Adjusted value
             seed  = gr.Slider(minimum=0, step=1, maximum=10000000, value=124, label="Seed Value")
-            num_inference_steps = gr.Slider(minimum=1, step=1, maximum=30, value=24, label="num_inference_steps")
-            true_guidance_scale = gr.Slider(minimum=1, step=1, maximum=10, value=3.5, label="true_guidance_scale")
+            num_inference_steps = gr.Slider(minimum=1, step=1, maximum=50, value=40, label="num_inference_steps")  # Adjusted value
+            true_guidance_scale = gr.Slider(minimum=1, step=1, maximum=10, value=7.0, label="true_guidance_scale")  # Adjusted value
 
 
 

controlnet_flux.py

@@ -45,10 +45,10 @@ class FluxControlNetModel(ModelMixin, ConfigMixin, PeftAdapterMixin):
         self,
         patch_size: int = 1,
         in_channels: int = 64,
-        num_layers: int = 19,
-        num_single_layers: int = 38,
-        attention_head_dim: int = 128,
-        num_attention_heads: int = 24,
+          num_layers: int = 24,
+        num_single_layers: int = 48,
+        attention_head_dim: int = 256,
+        num_attention_heads: int = 35,
         joint_attention_dim: int = 4096,
         pooled_projection_dim: int = 768,
         guidance_embeds: bool = False,

transformer_flux.py

@@ -278,10 +278,10 @@ class FluxTransformer2DModel(
         self,
         patch_size: int = 1,
         in_channels: int = 64,
-        num_layers: int = 19,
-        num_single_layers: int = 38,
-        attention_head_dim: int = 128,
-        num_attention_heads: int = 24,
+        num_layers: int = 24,
+        num_single_layers: int = 48,
+        attention_head_dim: int = 256,
+        num_attention_heads: int = 32,
         joint_attention_dim: int = 4096,
         pooled_projection_dim: int = 768,
         guidance_embeds: bool = False,