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import ktrain | |
import gradio as gr | |
from gradio.mix import Parallel | |
examples = [ | |
["I only get my kids the ones I got....I've turned down many so called 'vaccines'"], | |
["In child protective services, further providing for definitions, for immunity from liability"], | |
["Lol what? Measles is a real thing. Get vaccinated"]] | |
predictor_bert = ktrain.load_predictor('bert') | |
predictor_mental = ktrain.load_predictor('mentalbert') | |
predictor_phs = ktrain.load_predictor('phsbert') | |
def bert(text): | |
results = predictor_bert.predict(str(text)) | |
return str(results) | |
def mentalbert(text): | |
results = predictor_mental.predict(str(text)) | |
return str(results) | |
def phsbert(text): | |
results = predictor_phs.predict(str(text)) | |
return str(results) | |
bert_io = gr.Interface(fn=bert, inputs="text", outputs="text") | |
mental_io = gr.Interface(fn=mentalbert, inputs="text", outputs="text") | |
phs_io = gr.Interface(fn=phsbert, inputs="text", outputs="text") | |
Parallel(bert_io, mental_io, phs_io, | |
examples=examples, title="Vaccine Sentiment Task - VS2", | |
description="Enter vaccine-related tweets to generate sentiment from 3 models (BERT, MentalBERT, PHS-BERT). Label 0='vaccine critical', 1='neutral', 2='vaccine supportive'. The three provided examples are labelled 0,1,2 respectively. For details about VS2, refer to our paper (linked provided in https://huggingface.co/publichealthsurveillance/PHS-BERT).", | |
theme="peach").launch() | |