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| # import the main classes | |
| import gradio as gr | |
| import requests | |
| # input examples list | |
| ex_list = [["Women are not as capable as men in leadership roles."],["Women are capable as men in leadership roles."]] | |
| API_URL_Switch = "https://api-inference.huggingface.co/models/google/flan-t5-base" | |
| headers_Switch = {"Authorization": "Bearer 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"} | |
| def query_Switch(payload): | |
| response = requests.post(API_URL_Switch, headers=headers_Switch, json=payload) | |
| return response.json() | |
| def classify_gender_equality(input_sentence): | |
| # Here goes your code to classify gender equality from input_sentence | |
| # Return the result as a string | |
| # sub_text = 'Gender equality is important for the progress of society.' | |
| sub_text = input_sentence | |
| prompt = f"Please classify the this sentence ( {sub_text} ) as promoting or not promoting gender equality" | |
| output_temp = query_Switch({ | |
| "inputs": prompt, | |
| }) | |
| return "This sentence is " + output_temp[0]['generated_text'] + " for gender equality" | |
| input_text = gr.inputs.Textbox(label="Input Sentence", default="Women deserve equal pay") | |
| # Create the output text field | |
| output_text = gr.outputs.Textbox(label="Gender Equality Classification") | |
| # Create the Gradio interface | |
| gr.Interface(fn=classify_gender_equality, inputs=[input_text], outputs=output_text, title='Gender Equality Classification', examples = ex_list).launch() | |