Update app.py

app.py

@@ -1,12 +1,15 @@
 import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-# Load model and tokenizer
 model_name = "deepseek-ai/DeepSeek-V3"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    trust_remote_code=True,
+    device_map="auto",
+    quantization_config=None
+)
 
-# Function to handle chatbot response
 def chat_with_deepseek(prompt):
     inputs = tokenizer(prompt, return_tensors="pt")
     outputs = model.generate(
@@ -18,16 +21,11 @@ def chat_with_deepseek(prompt):
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return response
 
-# Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("# DeepSeek Chatbot")
-    with gr.Row():
-        with gr.Column():
-            user_input = gr.Textbox(label="Enter your message", placeholder="Type something...")
-        with gr.Column():
-            submit_btn = gr.Button("Send")
-    chatbot_output = gr.Textbox(label="Response", placeholder="Chatbot response will appear here")
-    
+    user_input = gr.Textbox(label="Enter your message")
+    chatbot_output = gr.Textbox(label="Response")
+    submit_btn = gr.Button("Send")
     submit_btn.click(chat_with_deepseek, inputs=user_input, outputs=chatbot_output)
 
 demo.launch()