Delete app.py

app.py

@@ -1,32 +0,0 @@
-import gradio as gr
-from diffusers import DiffusionPipeline
-import torch
-from PIL import Image
-
-# Load the pipeline
-prj_path = "jkcg/furniture-chair"
-model = "stabilityai/stable-diffusion-xl-base-1.0"
-pipe = DiffusionPipeline.from_pretrained(
-     model,
-     torch_dtype=torch.float32,  # Use float32 for CPU
-)
-pipe.to("cpu")  # Ensure the pipeline runs on CPU
-pipe.load_lora_weights(prj_path, weight_name="pytorch_lora_weights.safetensors")
-
-def generate_image(prompt, seed):
-    generator = torch.Generator("cpu").manual_seed(seed)
-    image = pipe(prompt=prompt, generator=generator).images[0]
-    return image
-
-# Create the Gradio interface
-interface = gr.Interface(
-    fn=generate_image,
-    inputs=[
-        gr.Textbox(label="Prompt", value="photo of a furnichair-texx in an empty room"),
-        gr.Slider(label="Seed", minimum=0, maximum=10000, step=1, value=42)
-    ],
-    outputs=gr.Image(label="Generated Image")
-)
-
-# Launch the interface
-interface.launch(share=True)