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## import gradio | |
import gradio as gr | |
## install the transformer pipeline | |
from transformers import pipeline | |
from transformers import AutoModelWithLMHead,AutoTokenizer | |
mode_name = 'liam168/trans-opus-mt-en-zh' | |
model = AutoModelWithLMHead.from_pretrained(mode_name) | |
tokenizer = AutoTokenizer.from_pretrained(mode_name) | |
pipe_ch = pipeline("translation_en_to_zh", model=model, tokenizer=tokenizer) | |
def translate_ch(text): | |
return pipe_ch(text)[0]["translation_text"] | |
with gr.Blocks() as demo: | |
with gr.Row(): | |
with gr.Column(): | |
english = gr.Textbox(label="English text") | |
translate_btn = gr.Button(value="Translate") | |
with gr.Column(): | |
chinese = gr.Textbox(label="Chinese Text") | |
translate_btn.click(translate_ch, inputs=english, outputs=chinese, api_name="translate-to-chinese") | |
examples = gr.Examples(examples=["I like to study Data Science and Machine Learning.", "Helen is a good swimmer."], | |
inputs=[english]) | |
demo.launch() |