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