Create app.py
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app.py
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app.py
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runaksh
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Update app.py
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about 2 months ago
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1.33 kB
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# -*- coding: utf-8 -*-
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"""gradio_deploy.ipynb
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Automatically generated by Colaboratory.
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"""
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import os
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import gradio
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from PIL import Image
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from timeit import default_timer as timer
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from tensorflow import keras
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import torch
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
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import numpy as np
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loaded_model = AutoModelForSequenceClassification.from_pretrained("runaksh/financial_sentiment_distilBERT")
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loaded_tokenizer = AutoTokenizer.from_pretrained("runaksh/financial_sentiment_distilBERT")
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# Function for class prediction
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def predict(sample, validate=True):
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classifier = pipeline("text-classification", model=loaded_model, tokenizer=loaded_tokenizer)
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pred = classifier(sample)[0]['label']
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return pred
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title = "Financial Sentiment Classification"
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description = "Enter the news"
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# Gradio elements
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# Input from user
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in_prompt = gradio.components.Textbox(lines=2, label='Enter the News')
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# Output response
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out_response = gradio.components.Textbox(label='Sentiment')
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# Gradio interface to generate UI link
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iface = gradio.Interface(fn=predict,
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inputs = in_prompt,
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outputs = out_response,
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title=title,
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description=description
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)
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iface.launch(debug = True)
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