This EdrawMax diagram offers a detailed representation of a BERT model applied to a NER task, showcasing the flow from Nepali text input through the BERT tokenizer to the encoder's representation and output tags like B-PERSON. The model processes input embeddings, transforming text data into a format that the machine learning model can interpret for identifying named entities. The template is a crucial tool for data scientists, linguists, and AI developers working in natural language processing, aiming to understand or explain the BERT model's complex mechanisms for tagging entities within text data.
