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import requests
import streamlit as st
import streamlit.components.v1 as components
def semanticComparativeClassification():
print('Pregunta ',st.session_state.mytext)
#API_URL = "https://api-inference.huggingface.co/models/Maite89/Roberta_finetuning_semantic_similarity_stsb_multi_mt"
API_URL = "https://api-inference.huggingface.co/models/symanto/sn-xlm-roberta-base-snli-mnli-anli-xnli"
headers = {"Authorization": "Bearer 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"}
def query(payload):
response = requests.post(API_URL, headers=headers, json=payload)
return response.json()
output = query({
"inputs": {
"wait_for_model" : True,
"source_sentence": st.session_state.mytext,
"sentences": [
"Conoces Lya2",
"He perdido la contraseña",
"Calendario de eventos",
"Cambios dobles",
"Cambios simples"
]
},
})
for i in output:
print(i)
return output
#x = st.slider('Select a value')
#st.write(x, 'squared is', x * x)
st.title('Uber pickups in NYC')
title = st.text_input('Query', '¿Conoces Lya2?', on_change=semanticComparativeClassification,key='mytext')
#st.write('The current movie title is', title) |