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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(value="One",label="Sentence 1") | |
| s2 = gr.Textbox(value="Two",label="Sentence 2") | |
| examples = gr.Examples( | |
| examples=[ | |
| ["one", "two"], | |
| ], | |
| inputs=[s1, s2], | |
| ) | |
| demo = gr.Interface(fn=infer, inputs=[s1,s2], outputs="text", | |
| title=title, | |
| description=desc, | |
| article=long_desc) | |
| demo.launch() | |