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import gradio as gr | |
from transformers import BartForSequenceClassification, BartTokenizer | |
# model = pipeline("text-generation") | |
# following https://joeddav.github.io/blog/2020/05/29/ZSL.html | |
tokenizer_bart = BartTokenizer.from_pretrained('facebook/bart-large-mnli') | |
model_bart_sq = BartForSequenceClassification.from_pretrained('facebook/bart-large-mnli') | |
title="Stance Detection using Zero Shot" | |
description="Welcome to the side where the grass is greener. This is a simple tool which was created with an aim to stance towards a given entity in a sentence. However, this is not the only use case of it!" | |
def zs(premise,hypothesis): | |
input_ids = tokenizer_bart.encode(premise, hypothesis, return_tensors='pt') | |
logits = model_bart_sq(input_ids)[0] | |
# entail_contradiction_logits = logits[:,[0,1,2]] | |
entail_contradiction_logits = logits[:,[0,2]] | |
probs = entail_contradiction_logits.softmax(dim=1) | |
contra_prob = round(probs[:,0].item(),4) | |
# neut_prob = round(probs[:,1].item(),4) | |
entail_prob = round(probs[:,1].item(),4) | |
# return contra_prob, neut_prob, entail_prob | |
return contra_prob, entail_prob | |
# gr.Interface(fn=zs, inputs=["text", "text"], outputs=["text","text","text"]).launch() | |
with gr.Blocks() as demo: | |
gr.Examples( | |
examples = [["Roger Federer is an amazing Tennis Player","The stance to Roger Federer is positive."]], | |
inputs = [["Roger Federer is an amazing Tennis Player","The stance to Roger Federer is positive."]] | |
) | |
gr.Markdown(f"# {title}") | |
gr.Markdown(f"## {description}") | |
with gr.Row(): | |
premise = gr.Textbox(label="Premise",placeholder = "Roger Federer is an amazing Tennis Player") | |
hypothesis = gr.Textbox(label="Hypothesis", placeholder = "The stance to Roger Federer is positive.") | |
with gr.Row(): | |
greet_btn = gr.Button("Compute") | |
with gr.Row(): | |
entailment = gr.Textbox(label="Entailment Probability") | |
contradiction = gr.Textbox(label="Contradiction Probability") | |
# neutral = gr.Textbox(label="Neutral Probability") | |
# greet_btn.click(fn=zs, inputs=[premise,hypothesis], outputs=[contradiction,neutral,entailment]) | |
greet_btn.click(fn=zs, inputs=[premise,hypothesis], outputs=[contradiction,entailment]) | |
demo.launch() |