Update app.py

app.py

@@ -9,6 +9,15 @@ from transformers import TextIteratorStreamer
 
 import spaces
 
+
+PLACEHOLDER = """
+<div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;">
+   <img src="https://cdn-uploads.huggingface.co/production/uploads/64ccdc322e592905f922a06e/DDIW0kbWmdOQWwy4XMhwX.png" style="width: 80%; max-width: 550px; height: auto; opacity: 0.55;  "> 
+   <h1 style="font-size: 28px; margin-bottom: 2px; opacity: 0.55;">LLaVA-Llama-3-8B</h1>
+   <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.65;">Llava-Llama-3-8b is a LLaVA model fine-tuned from Meta-Llama-3-8B-Instruct and CLIP-ViT-Large-patch14-336 with ShareGPT4V-PT and InternVL-SFT by XTuner</p>
+</div>
+"""
+
 model_id = "xtuner/llava-llama-3-8b-v1_1-transformers"
 
 processor = AutoProcessor.from_pretrained(model_id)
@@ -78,13 +87,14 @@ def bot_streaming(message, history):
 
 demo = gr.ChatInterface(
     fn=bot_streaming,
-    fill_height=False,
+    fill_height=True,
     title="LLaVA Llama-3-8B",
     examples=[{"text": "What is on the flower?", "files": ["./bee.jpg"]},
               {"text": "How to make this pastry?", "files": ["./baklava.png"]}],
     description="Try [LLaVA Llama-3-8B](https://huggingface.co/xtuner/llava-llama-3-8b-v1_1-transformers). Upload an image and start chatting about it, or simply try one of the examples below. If you don't upload an image, you will receive an error.",
     stop_btn="Stop Generation",
-    multimodal=True
+    multimodal=True, 
+    placeholder=PLACEHOLDER,
 )
 
 demo.queue(api_open=False)