Update app.py

app.py

@@ -4,7 +4,7 @@ from transformers import AutoConfig, AutoModelForCausalLM
 from janus.models import MultiModalityCausalLM, VLChatProcessor
 from PIL import Image
 import numpy as np
-import spaces  # Ensure this is available
+import spaces  # Import spaces for ZeroGPU compatibility
 
 # Load the model and processor
 model_path = "deepseek-ai/Janus-Pro-7B"
@@ -99,7 +99,18 @@ def generate_image(prompt, seed=None, guidance=5, t2i_temperature=1.0):
 # Gradio interface
 def create_interface():
     with gr.Blocks() as demo:
-        gr.Markdown("# Text-to-Image Generation")
+        gr.Markdown("""
+        # Text-to-Image Generation with Janus-Pro-7B
+
+        Welcome to the Janus-Pro-7B Text-to-Image Generator! This advanced AI model by DeepSeek offers state-of-the-art capabilities in generating images from textual descriptions. Leveraging a unified multimodal framework, Janus-Pro-7B excels in both understanding and generating content, providing detailed and accurate visual representations based on your prompts.
+
+        **Key Features:**
+        - **Unified Multimodal Framework:** Integrates visual encoding and language processing for seamless understanding and generation.
+        - **High-Quality Image Generation:** Produces stable and detailed images that often surpass those from other leading models.
+        - **Flexible and Efficient:** Designed for a wide range of applications, from creative image generation to detailed visualizations.
+
+        For more information about Janus-Pro-7B, visit the [official Hugging Face model page](https://huggingface.co/deepseek-ai/Janus-Pro-7B).
+        """)
         
         prompt_input = gr.Textbox(label="Prompt (describe the image)")
         seed_input = gr.Number(label="Seed (Optional)", value=12345, precision=0)