|
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
|
from transformers import pipeline |
|
import gradio as gr |
|
|
|
|
|
|
|
model_name = "Helsinki-NLP/opus-mt-en-zh" |
|
tokenizer = AutoTokenizer.from_pretrained(model_name) |
|
|
|
pipe = pipeline("translation", model=model_name, tokenizer=tokenizer) |
|
|
|
|
|
|
|
|
|
|
|
def getTranslateResult(inputTextValue): |
|
testRes = pipe(inputTextValue) |
|
return testRes[0]["translation_text"] |
|
|
|
|
|
|
|
|
|
with gr.Blocks() as translateDemo: |
|
with gr.Row(): |
|
with gr.Column(): |
|
inputText = gr.Textbox(label="Please enter the translation content, only Chinese is supported...") |
|
submitBtn = gr.Button(variant="primary", value="Submit") |
|
outText = gr.Textbox(label='Translation results are shown here...') |
|
|
|
|
|
inputText.submit( |
|
fn=getTranslateResult, |
|
inputs=inputText, |
|
outputs=outText |
|
) |
|
|
|
submitBtn.click( |
|
fn=getTranslateResult, |
|
inputs=inputText, |
|
outputs=outText |
|
) |
|
|
|
translateDemo.queue().launch() |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
