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import os | |
API_TOKEN = os.getenv('API_TOKEN') | |
import gradio as gr | |
import requests | |
API_URL = "https://api-inference.huggingface.co/models/tlkh/flan-t5-paraphrase-classify-explain" | |
headers = {"Authorization": f"Bearer {API_TOKEN}"} | |
def query(payload): | |
response = requests.post(API_URL, headers=headers, json=payload) | |
return response.json() | |
def infer(s1, s2): | |
model_input = "Classify and explain the relationship between this pair of sentences: <S1> "+s1+" </S1><S2> "+s2+" </S2>" | |
data = query(model_input) | |
if "error" in data: | |
return "Error: "+ data["error"] | |
elif "generated_text" in data[0]: | |
return data["generated_text"] | |
else: | |
return data | |
title = "Paraphrase Classification and Explanation" | |
desc = "Classify and explain the semantic relationship between the two sentences" | |
long_desc = "This is a Flan-T5-Large model fine-tuned to perform paraphrase classification and explanation. It takes in two sentences as inputs." | |
example1 = ["On Monday, Tom went to the market.","Tom went to the market on Monday."] | |
s1 = gr.Textbox(label="Sentence 1") | |
s2 = gr.Textbox(label="Sentence 2") | |
demo = gr.Interface(fn=infer, inputs=[s1,s2], outputs="text", | |
examples=gr.Examples(examples=[example1],inputs=[s1,s2]), | |
title=title, | |
description=desc, | |
article=long_desc) | |
demo.launch() | |