| import gradio as gr |
| from transformers import pipeline |
| from transformers import AutoTokenizer, AutoModelForTokenClassification |
| tokenizer = AutoTokenizer.from_pretrained("51la5/roberta-large-NER") |
| model = AutoModelForTokenClassification.from_pretrained("51la5/roberta-large-NER") |
| classifier = pipeline("ner", model=model, tokenizer=tokenizer,grouped_entities=True) |
|
|
| def get_ner(text): |
| output = classifier(text) |
| for elm in output: |
| elm['entity'] = elm['entity_group'] |
| return {"text": text, "entities": output} |
|
|
|
|
| demo = gr.Interface(fn=get_ner, |
| title="Atoqli nomlarni topish(NER)", |
| inputs=gr.Textbox(lines=4, placeholder="Matinni kiriting!", label="Matn*"), |
| outputs=gr.HighlightedText(label="Natija:") |
| ) |
|
|
| demo.launch() |
