import gradio as gr from transformers import pipeline # Load the pre-trained NER model model = pipeline("ner", model="/home/user/app/mendobert/", tokenizer="indolem/indobert-base-uncased") # basemodel = pipeline("ner", model="/home/user/app/base-model/", tokenizer="indolem/indobert-base-uncased") def text_analysis(text): doc = model(text) pos_tokens = [] for token in doc: pos_tokens.extend([(token.text, token.pos_), (" ", None)]) return pos_tokens, pos_count, html demo = gr.Interface( text_analysis, gr.Textbox(placeholder="Enter sentence here..."), ["highlight", "json", "html"], examples=[ ["Aspartylglucosaminuria (AGU) adalah gangguan metabolisme glikoprotein langka."], ["Mutasi germ - line dari gen BRCA1 membuat wanita cenderung mengalami kanker payudara dini dengan mengorbankan fungsi presumtif gen sebagai penekan tumor."], ], ) demo.launch()