| import torch |
| import gradio as gr |
| import json |
| from transformers import pipeline |
|
|
| |
| text_translator = pipeline("translation", model="facebook/nllb-200-distilled-600M", |
| torch_dtype=torch.bfloat16) |
|
|
| |
| with open('language.json', 'r') as file: |
| language_data = json.load(file) |
|
|
| |
| def get_FLORES_code_from_language(language): |
| for entry in language_data: |
| if entry['Language'].lower() == language.lower(): |
| return entry['FLORES-200 code'] |
| return None |
|
|
| |
| def translate_text(text, destination_language): |
| dest_code = get_FLORES_code_from_language(destination_language) |
| if not dest_code: |
| return f"❌ Language code for '{destination_language}' not found." |
| translation = text_translator(text, src_lang="eng_Latn", tgt_lang=dest_code) |
| return translation[0]["translation_text"] |
|
|
| |
| language_list = [entry["Language"] for entry in language_data] |
|
|
| |
| with gr.Blocks(theme=gr.themes.Default()) as demo: |
| gr.Markdown( |
| """ |
| # 🌐 Multilingual Translator — Powered by Meta NLLB-200 |
| Translate English text into 200+ languages using the FLORES-200 dataset. |
| """ |
| ) |
|
|
| with gr.Row(): |
| input_text = gr.Textbox(label="📝 English Input", lines=6, placeholder="Type your English sentence here...") |
| output_lang = gr.Dropdown(choices=language_list, label="🌍 Target Language") |
|
|
| output_text = gr.Textbox(label="✅ Translated Output", lines=4) |
|
|
| translate_btn = gr.Button("🔄 Translate") |
|
|
| translate_btn.click(fn=translate_text, inputs=[input_text, output_lang], outputs=output_text) |
|
|
| gr.Markdown( |
| """ |
| --- |
| 🧠 Model: `facebook/nllb-200-distilled-600M` |
| 🌐 Language codes from [FLORES-200](https://github.com/facebookresearch/flores) |
| """ |
| ) |
|
|
| demo.launch() |
