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# -*- coding: utf-8 -*-
"""app_creation.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1sguK4GohScbDFj7Toyodw7faqhPrfc1a
"""
import json
import torch
import gradio as gr
import onnxruntime as rt
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
with open("encoded_keywords.json", "r") as fp:
encode_keywords = json.load(fp)
keywords = list(encode_keywords.keys())
inf_session = rt.InferenceSession('bert_quantized.onnx')
input_name = inf_session.get_inputs()[0].name
output_name = inf_session.get_outputs()[0].name
def classify_keywords(abstract):
input_ids = tokenizer(abstract)['input_ids'][:512]
logits = inf_session.run([output_name], {
input_name: [input_ids]
})[0]
logits = torch.FloatTensor(logits)
probs = torch.sigmoid(logits)[0]
return dict(zip(keywords, map(float, probs)))
label = gr.Label(num_top_classes = 5)
interface = gr.Interface(
fn = classify_keywords,
inputs = "text",
outputs = label
)
interface.launch()
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