Update app.py

app.py

@@ -1,16 +1,10 @@
-from transformers import AutoModel, AutoTokenizer
-import torch
-
-# Load the model and tokenizer manually
-model = AutoModel.from_pretrained("tejani/TileTexture")
-tokenizer = AutoTokenizer.from_pretrained("tejani/TileTexture")
+from transformers import DiffusionPipeline  # Example for diffusion models
+import gradio as gr
 
-# Define a custom function (adjust based on model purpose)
-def generate_output(input_text):
-    inputs = tokenizer(input_text, return_tensors="pt")
-    outputs = model(**inputs)
-    return outputs  # Process outputs as needed
+model = DiffusionPipeline.from_pretrained("tejani/TileTexture")
+def generate_image(text):
+    image = model(text).images[0]  # Adjust based on output structure
+    return image
 
-import gradio as gr
-interface = gr.Interface(fn=generate_output, inputs="text", outputs="text")
+interface = gr.Interface(fn=generate_image, inputs="text", outputs="image")
 interface.launch()