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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.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])
gr.Examples(
examples = [["Roger Federer is an amazing Tennis Player","The stance to Roger Federer is positive."]],
inputs = [["Premise","Hypothesis"]]
)
demo.launch() |