import gradio as gr import os import requests import time from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline import paddlehub as hub HF_TOKEN = os.environ["HF_TOKEN"] model = hub.Module(name='ernie_vilg') def get_ernie_vilg(text_prompts, style): style = style.split('-')[0] results = model.generate_image(text_prompts=text_prompts, style=style, visualization=False) return results[0] sd_inf = gr.Blocks.load(name="spaces/stabilityai/stable-diffusion", use_auth_token=HF_TOKEN) nllb_model_name = 'facebook/nllb-200-distilled-600M' nllb_model = AutoModelForSeq2SeqLM.from_pretrained(nllb_model_name) nllb_tokenizer = AutoTokenizer.from_pretrained(nllb_model_name) def get_chinese_translation(text): #in_language_first, in_language_second, print("********Inside get_chinese_translation ********") src = 'eng_Latn' tgt= 'zho_Hans' print(f"text is :{text}, source language is : {src}, target language is : {tgt} ") translator = pipeline('translation', model=nllb_model, tokenizer=nllb_tokenizer, src_lang=src, tgt_lang=tgt) output = translator(text, max_length=400) print(f"initial output is:{output}") output = output[0]['translation_text'] print(f"output is:{output}") return output #Block inference not working for stable diffusion def get_sd(translated_txt, samples, steps, scale, seed): print("******** Inside get_SD ********") print(f"translated_txt is : {translated_txt}") sd_img_gallery = sd_inf(translated_txt, samples, steps, scale, seed, fn_index=1)[0] return sd_img_gallery demo = gr.Blocks() with demo: gr.Markdown("

ERNIE in English !

") gr.Markdown("

ERNIE-ViLG is a state-of-the-art text-to-image model that generates images from simplified Chinese text.

") gr.Markdown("

This app helps you in checking-out ERNIE in English. Note that due to limitations on available Ram, only one image is being generated at the moment

Please access the original model here - [ERNIE-ViLG](https://huggingface.co/spaces/PaddlePaddle/ERNIE-ViLG)

") with gr.Row(): with gr.Column(): in_text_prompt = gr.Textbox(label="Enter English text here") out_text_chinese = gr.Textbox(label="Text in Simplified Chinese") b1 = gr.Button("English to Simplified Chinese") #s1 = gr.Slider(label='samples', value=4, visible=False) #s2 = gr.Slider(label='steps', value=45, visible=False) #s3 = gr.Slider(label='scale', value=7.5, visible=False) #s4 = gr.Slider(label='seed', value=1024, visible=False) with gr.Row(): with gr.Column(): in_styles = gr.Dropdown(['水彩-WaterColor', '油画-OilPainting', '粉笔画-Painting', '卡通-Cartoon', '蜡笔画-Pencils', '儿童画-ChildrensPaintings', '探索无限-ExploringTheInfinite']) b2 = gr.Button("Generate Images from Ernie") out_ernie = gr.Image(type="pil", label="Ernie output for the given prompt") #out_gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery") #.style(grid=[2, 3], height="auto") #in_language_first = gr.Textbox(visible=False, value= 'eng_Latn') #'English' #in_language_second = gr.Textbox(visible=False, value= 'zho_Hans') #'Chinese (Simplified)' #out_sd = gr.Image(type="pil", label="SD output for the given prompt") #b3 = gr.Button("Generate Images from SD") b1.click(get_chinese_translation, in_text_prompt, out_text_chinese ) #[in_language_first, in_language_second, b2.click(get_ernie_vilg, [out_text_chinese, in_styles], out_ernie) #b3.click(get_sd, [in_text_prompt,s1,s2,s3,s4], out_sd) #out_gallery ) demo.launch(enable_queue=True, debug=True)