NLP Node Catalog
NLP category
Generated from 2 catalog nodes in AI/ML/ONNX/NLP.
Nodes in this category
Showing 2 of 2 generated node docs.
Named Entity Recognition
AI/ML/ONNX/NLPExtract named entities (persons, organizations, locations, dates, etc.) from text using ONNX models. Supports BERT, RoBERTa, and other transformer-based NER models with automatic tokenization. Download models from: BERT-base-NER (https://huggingface.co/dslim/bert-base-NER), Multilingual NER (https://huggingface.co/Davlan/bert-base-multilingual-cased-ner-hrl), spaCy NER (https://huggingface.co/spacy). Text longer than the model's window is split into overlapping chunks rather than truncated, so entities are found throughout a long document. Download tokenizer.json and config.json from the same model repository — config.json carries the id2label mapping that names the entity types and the sequence length the model accepts.
Zero-Shot NER (GLiNER)
AI/ML/ONNX/NLPExtract entities for any labels you name at runtime, with no fixed label set and no retraining. Load a GLiNER ONNX export (e.g. https://huggingface.co/onnx-community/gliner_small-v2.1, gliner_multi-v2.1, gliner_medium_news-v2.1, gliner_multi_pii-v1, NuNER_Zero) plus the tokenizer.json from the same repository. For models with a fixed label set, use the Named Entity Recognition node instead.