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from transformers import BartForSequenceClassification, BartTokenizer | |
import gradio as grad | |
bart_tkn = BartTokenizer.from_pretrained('facebook/bart-large-mnli') | |
mdl = BartForSequenceClassification.from_pretrained('facebook/bart-large-mnli') | |
def classify(text,label): | |
tkn_ids = bart_tkn.encode(text, label, return_tensors='pt') | |
tkn_lgts = mdl(tkn_ids)[0] | |
entail_contra_tkn_lgts = tkn_lgts[:,[0,2]] | |
probab = entail_contra_tkn_lgts.softmax(dim=1) | |
response = probab[:,1].item() * 100 | |
return response | |
txt=grad.Textbox(lines=1, label="English", placeholder="text to be classified") | |
labels=grad.Textbox(lines=1, label="Label", placeholder="Input a Label") | |
out=grad.Textbox(lines=1, label="Probablity of label being true is") | |
grad.Interface(classify, inputs=[txt,labels], outputs=out).launch() |