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import gradio as gr
import requests
import json
import os
LANGUAGES = ['Akan', 'Arabic', ' Assamese', 'Bambara', 'Bengali', 'Catalan', 'English', 'Spanish', ' Basque', 'French', ' Gujarati', 'Hindi',
'Indonesian', 'Igbo', 'Kikuyu', 'Kannada', 'Ganda', 'Lingala', 'Malayalam', 'Marathi', 'Nepali', 'Chichewa', 'Oriya', 'Panjabi', 'Portuguese',
'Kirundi', 'Kinyarwanda', 'Shona', 'Sotho', 'Swahili', 'Tamil', 'Telugu', 'Tswana', 'Tsonga', 'Twi', 'Urdu', 'Viêt Namese', 'Wolof', 'Xhosa',
'Yoruba', 'Chinese', 'Zulu']
API_URL = "https://api-inference.huggingface.co/models/bigscience/mt0-xxl"
def translate(output, text):
"""Translate text from input language to output language"""
instruction = f"""Translatate to {output}: {text}\nTranslation: """
json_ = {
"inputs": instruction,
"parameters": {
"return_full_text": True,
"do_sample": False,
"max_new_tokens": 250,
},
"options": {
"use_cache": True,
"wait_for_model": True,
},
}
response = requests.request("POST", API_URL, json=json_)
output = response.json()[0]['generated_text']
return output.replace(instruction, '', 1)
demo = gr.Blocks()
with demo:
gr.Markdown("<h1><center>Translation with Bloom</center></h1>")
gr.Markdown("<center>Translation in many language with mt0-xxl</center>")
with gr.Row():
output_lang = gr.Dropdown(LANGUAGES, value='French', label='Select output language')
input_text = gr.Textbox(label="Input", lines=6)
output_text = gr.Textbox(lines=6, label="Output")
buton = gr.Button("translate")
buton.click(translate, inputs=[output_lang, input_text], outputs=output_text)
demo.launch(enable_queue=True, debug=True)
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