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| import gradio as gr | |
| from transformers import pipeline | |
| # pipeline_en = pipeline(task="text2text-generation", model="beyond/genius-large") | |
| # pipeline_en = pipeline_zh | |
| pipeline_zh = pipeline(task="text2text-generation", model="beyond/genius-base-chinese") | |
| def predict_en(sketch): | |
| # generated_text = pipeline_en(sketch, num_beams=3, do_sample=True, max_length=200)[0]['generated_text'] | |
| # return generated_text | |
| return "The English model (`genius-large`) to too large to be maintained in a free space, please download the model checkpoint and run locally." | |
| def predict_zh(sketch): | |
| generated_text = pipeline_zh(sketch, num_beams=3, do_sample=True, max_length=200)[0]['generated_text'] | |
| return generated_text.replace(' ','') | |
| with gr.Blocks() as demo: | |
| gr.Markdown(""" | |
| # 💡GENIUS – generating text using sketches! | |
| [Please check our GitHub repo for more details.](https://github.com/beyondguo/genius) | |
| We provide both English and Chinese GENIUS models. | |
| - For English version, the mask token is `<mask>`; | |
| - For Chinese version, the mask token is `[MASK]`. | |
| """) | |
| with gr.Tab("English"): | |
| input1 = gr.Textbox(lines=5, value="<mask> Conference on Empirical Methods <mask> submission of research papers <mask> Deep Learning <mask>") | |
| output1 = gr.Textbox(lines=5) | |
| button1 = gr.Button("Generate") | |
| with gr.Tab("Chinese"): | |
| input2 = gr.Textbox(lines=5, value="自然语言处理[MASK]谷歌公司[MASK]通用人工智能[MASK]") | |
| output2 = gr.Textbox(lines=5) | |
| output2 = output2 | |
| button2 = gr.Button("Generate") | |
| # with gr.Accordion("Open for More!"): | |
| # gr.Markdown("Look at me...") | |
| button1.click(predict_en, inputs=input1, outputs=output1) | |
| button2.click(predict_zh, inputs=input2, outputs=output2) | |
| demo.launch() |