| from transformers import pipeline | |
| import gradio as gr | |
| model_checkpoint = "MuntasirHossain/bert-finetuned-ner" | |
| model = pipeline("ner", model=model_checkpoint, aggregation_strategy="simple") | |
| def ner(text): | |
| output = model(text) | |
| return {"text": text, "entities": output} | |
| description = "This AI model is trained to identify and classify named entities such as persons (PER), locations (LOC), organizations (ORG) and miscellaneous (MISC) \ | |
| in unstructured text." | |
| title = "Named Entity Recognition" | |
| theme = "grass" | |
| examples=["Mount Everest is Earth's highest mountain, located in the Mahalangur Himal sub-range of the Himalayas. Edmund Hillary and Tenzing Norgay were the \ | |
| first climbers confirmed to have reached the summit of Mount Everest on May 29, 1953."] | |
| gr.Interface(ner, | |
| gr.Textbox(placeholder="Enter sentence here..."), | |
| gr.HighlightedText(), | |
| title=title, | |
| theme = theme, | |
| description=description, | |
| examples=examples).launch() |