Update app.py

app.py

@@ -1,5 +1,4 @@
 import gradio as gr
-import spaces
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 # Load model and tokenizer
@@ -7,34 +6,25 @@ model_name = "infly/OpenCoder-8B-Instruct"
 tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
 model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
 
-@spaces.GPU
+# Define the text generation function
 def generate_text(prompt):
     inputs = tokenizer(prompt, return_tensors="pt", truncation=True, padding=True)
-    outputs = model.generate(inputs["input_ids"], max_length=100, num_return_sequences=1)
+    outputs = model.generate(
+        inputs["input_ids"],
+        attention_mask=inputs["attention_mask"],  # Add attention mask
+        max_length=50,  # Reduce max_length to conserve memory
+        num_return_sequences=1
+    )
     return tokenizer.decode(outputs[0], skip_special_tokens=True)
 
+# Create the Gradio interface
 iface = gr.Interface(
     fn=generate_text,
-    inputs=[
-        gr.Textbox(label="Enter your prompt", placeholder="Start typing...", lines=5)
-        #gr.Slider(minimum=50, maximum=200, value=100, step=1, label="Max Length"),
-        #gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.1, label="Temperature"),
-    ],
+    inputs=gr.Textbox(label="Enter your prompt", placeholder="Start typing...", lines=5),
     outputs="text",
     title="OpenCoder 8B Instruct",
-    description="Generate text using the OpenCoder model. Adjust the settings and input a prompt to generate responses.",
+    description="Generate text using the OpenCoder model. Input a prompt to generate responses.",
 )
 
 # Launch the Gradio app
-iface.launch(share=True)
-    
-# Create Gradio interface
-# interface = gr.Interface(
-#     fn=generate_text,
-#     inputs=gr.Textbox(lines=2, placeholder="Enter your prompt here..."),
-#     outputs=gr.Textbox(label="Generated Text")
-# )
-
-# # Launch the Gradio app
-# if __name__ == "__main__":
-#     interface.launch()
+iface.launch()