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| import gradio as gr | |
| title = "MarianMT" | |
| description = "Gradio Demo for MarianMT. To use it, simply add your text, or click one of the examples to load them. Read more at the links below." | |
| article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1804.00344' target='_blank'>Marian: Fast Neural Machine Translation in C++</a></p>" | |
| examples = [ | |
| ['ζε«ζ²ε°ε€«εοΌζδ½ε¨ζζγ',"opus-mt-zh-en"] | |
| ] | |
| io1 = gr.Interface.load("huggingface/Helsinki-NLP/opus-mt-zh-en") | |
| io2 = gr.Interface.load("huggingface/Helsinki-NLP/opus-mt-en-de") | |
| def inference(text, model): | |
| if model == "opus-mt-zh-en": | |
| outtext = io1(text) | |
| else: | |
| outtext = io2(text) | |
| return outtext | |
| gr.Interface( | |
| inference, | |
| [gr.inputs.Textbox(label="Input"),gr.inputs.Dropdown(choices=["opus-mt-zh-en","opus-mt-en-de"], type="value", default="opus-mt-zh-en", label="model")], | |
| [gr.outputs.Textbox(label="Output")], | |
| examples=examples, | |
| article=article, | |
| title=title, | |
| description=description).launch(enable_queue=True) |