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import torch | |
import gradio as gr | |
from transformers import pipeline | |
# Use a pipeline as a high-level helper | |
from transformers import pipeline | |
code_writer = pipeline("text-generation", model="Qwen/Qwen2.5-Coder-7B-Instruct",torch_dtype=torch.bfloat16 ) | |
# Define the code generation function | |
def generate_code(prompt): | |
# Generate code based on the input prompt | |
output = code_writer(prompt, num_return_sequences=1, do_sample=True) | |
return output[0]['generated_text'] | |
# Close any existing Gradio instances | |
gr.close_all() | |
# Set up the Gradio interface | |
Demo = gr.Interface( | |
fn=generate_code, | |
inputs=[ | |
gr.Textbox(label="Code Prompt", lines=5, placeholder="Enter a description or snippet for code generation.") | |
], | |
outputs=[gr.Textbox(label="Generated Code", lines=10)], | |
title="Code_Generator_App", | |
description="This application generates code based on your input prompt." | |
) | |
# Launch the app with a public link | |
Demo.launch(share=True) | |