Spaces:
No application file
No application file
| from transformers import pipeline | |
| import gradio as gr | |
| #Recomendador trabajar o estudiar transformer | |
| generator = pipeline( | |
| "text2text-generation", | |
| model="google/flan-t5-small" | |
| ) | |
| def career_advice(age, academic_level, interests, needs_income): | |
| prompt = f""" | |
| You are an expert career advisor. A student has the following data: | |
| - Age: {age} | |
| - Academic level: {academic_level} | |
| - Interests: {interests} | |
| - Needs income: {needs_income} | |
| Give a clear, realistic, and motivating recommendation about whether the student should: | |
| - Continue studying | |
| - Do vocational training (FP) | |
| - Start working | |
| Explain the reasoning behind your recommendation. | |
| """ | |
| result = generator(prompt, max_length=200) | |
| return result[0]['generated_text'] | |
| interface = gr.Interface( | |
| fn=career_advice, | |
| inputs=[ | |
| gr.Number(label="Age"), | |
| gr.Textbox(label="Academic level"), | |
| gr.Textbox(label="Interests"), | |
| gr.Dropdown(choices=["Yes", "No"], label="Needs income") | |
| ], | |
| outputs=gr.Textbox(label="Recommendation"), | |
| title="Career Advisor for Students" | |
| ) | |
| interface.launch() | |