| | import gradio as gr |
| | from transformers import pipeline |
| |
|
| | |
| | print("Loading model...") |
| | pipe = pipeline( |
| | "text-generation", |
| | model="Qwen/Qwen2.5-Math-1.5B-Instruct", |
| | device_map="auto" |
| | ) |
| |
|
| | def generate_problems(topic, num_problems): |
| | prompt = f"""Generate {num_problems} math problems about {topic}. |
| | |
| | Format: |
| | Problem 1: [clear problem statement] |
| | Problem 2: [clear problem statement] |
| | |
| | Make them educational and challenging.""" |
| | |
| | result = pipe( |
| | prompt, |
| | max_new_tokens=1000, |
| | temperature=0.7, |
| | do_sample=True |
| | ) |
| | return result[0]['generated_text'] |
| |
|
| | |
| | demo = gr.Interface( |
| | fn=generate_problems, |
| | inputs=[ |
| | gr.Textbox(label="Topic", placeholder="algebra, calculus, geometry..."), |
| | gr.Slider(1, 10, value=3, step=1, label="Number of problems") |
| | ], |
| | outputs=gr.Textbox(label="Generated Problems", lines=20), |
| | title="Math Problem Generator", |
| | description="Generate math problems using AI" |
| | ) |
| |
|
| | demo.launch() |
