import gradio as gr from transformers import pipeline examples = [ 'Alisher Navoiy – ulug‘ o‘zbek va boshqa turkiy xalqlarning , mutafakkiri va davlat arbobi bo‘lgan.', 'Oʻzbekistonning poytaxti shahri boʻlib, davlat tili oʻzbek tili hisoblanadi.', 'Registon maydoni - tarixda shaharning ilm-fan, siyosat va markazi boʻlgan.', 'Venera - Quyosh tizimidagi o‘z o‘qi atrofida soat sohasi farqli ravishda aylanadigan yagona .', 'Kuchli yomg‘irlar tufayli bir qator kuchli sel oqishi kuzatildi.', 'Oʻzbekiston iqtisodiyoti bozor bosqichma-bosqich oʻtadi, tashqi savdo siyosati import oʻrnini bosishga asoslangan.' ] models = [ "sinonimayzer/UzRoBERTa-v1", "sinonimayzer/UzRoBERTa-v2", "sinonimayzer/UzRoBERTa-v3", "rifkat/uztext-3Gb-BPE-Roberta", "tahrirchi/tahrirchi-bert-base", ] def df(arr): d = {} for val in arr: d[val['token_str']] = val['score'] return d def fn(text): arr = [] for model in models: arr.append(df(pipeline("fill-mask", model=model)(text))) return arr[0], arr[1], arr[2], arr[3], arr[4] with gr.Blocks() as demo: with gr.Row(): with gr.Column(): output0 = gr.Label(label=models[0]) with gr.Column(): output1 = gr.Label(label=models[1]) with gr.Column(): output2 = gr.Label(label=models[2]) with gr.Row(): with gr.Column(): output3 = gr.Label(label=models[3]) with gr.Column(): output4 = gr.Label(label=models[4]) with gr.Column(): input = gr.Textbox(label="Input", value=examples[0], lines=8, max_lines=8) btn = gr.Button("Check") gr.Examples(examples, fn=fn, inputs=[input], outputs=[output0, output1, output2, output3, output4], cache_examples=True, batch=True) btn.click(fn, inputs=[input], outputs=[output0, output1, output2, output3, output4]) if __name__ == "__main__": demo.queue().launch()