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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() |