| 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) |
|
|
