Spaces:
Runtime error
Runtime error
| import os | |
| import torch | |
| import gradio as gr | |
| import time | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline | |
| model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-distilled-1.3B") | |
| tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-200-distilled-1.3B") | |
| def translation(source, target, text) -> str: | |
| translator = pipeline('translation', model=model, tokenizer=tokenizer, src_lang=source, tgt_lang=target) | |
| output = translator(text, max_length=400) | |
| output = output[0]['translation_text'] | |
| return output | |
| if __name__ == '__main__': | |
| # define gradio demo | |
| lang_codes = ["eng_Latn", "fuv_Latn", "fra_Latn", "arb_Arab"] | |
| #inputs = [gr.inputs.Radio(['nllb-distilled-600M', 'nllb-1.3B', 'nllb-distilled-1.3B'], label='NLLB Model'), | |
| inputs = [gr.inputs.Dropdown(lang_codes, default='fra_Latn', label='Source'), | |
| gr.inputs.Dropdown(lang_codes, default='fuv_Latn', label='Target'), | |
| gr.inputs.Textbox(lines=5, label="Input text"), | |
| ] | |
| title = "Fulfulde translator" | |
| demo_status = "Demo is running on CPU" | |
| description = "Fulfulde to French, English or Arabic and vice-versa translation demo using NLLB." | |
| examples = [ | |
| ['fra_Latn', 'fuv_Latn', 'La traduction est une tâche facile.'] | |
| ] | |
| gr.Interface( | |
| translation, | |
| inputs, | |
| ["text"], | |
| examples=examples, | |
| cache_examples=False, | |
| title=title, | |
| description=description | |
| ).launch() | |