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# Workaround to install the lib without "setup.py" | |
import sys | |
from git import Repo | |
Repo.clone_from("https://github.com/dimitreOliveira/hub.git", "./hub") | |
sys.path.append("/hub") | |
import gradio as gr | |
import tensorflow as tf | |
import tensorflow_text as text # Registers the ops. (needed for "bert_preprocessor") | |
from hub.tensorflow_hub.hf_utils import pull_from_hub | |
def model_fn(preprocessor, encoder): | |
text_input = tf.keras.layers.Input(shape=(), dtype=tf.string) | |
encoder_inputs = preprocessor(text_input) | |
outputs = encoder(encoder_inputs) | |
pooled_output = outputs["pooled_output"] | |
return tf.keras.Model(text_input, pooled_output) | |
def predict_fn(text): | |
print(text) | |
print(tf.constant([text])) | |
embed = model(tf.constant([text]))[0].numpy() | |
return embed | |
preprocessor = pull_from_hub(repo_id="Dimitre/bert_en_cased_preprocess") | |
encoder = pull_from_hub(repo_id="Dimitre/bert_en_cased_L-12_H-768_A-12") | |
model = model_fn(preprocessor, encoder) | |
iface = gr.Interface(fn=predict_fn, | |
title="BERT sentence embeddings", | |
description="Get the embeddings from your sentences using BERT", | |
inputs=gr.Textbox(lines=2, placeholder="Text input here...", label="Text"), | |
outputs="text", | |
examples=[["Hello! This is a random sentence"]]) | |
iface.launch() |