NLP Architect is an open source Python library for exploring state-of-the-art deep learning topologies and techniques for Natural Language Processing and Natural Language Understanding.
NLP Architect’s main purpose is to provide easy usage of NLP and NLU models while providing state-of-art and robust implementation.
Each of the models includes a comprehensive description on algorithms, network topologies, reference dataset descriptions and loader, and evaluation results.
Key Features
- Core NLP models used in many NLP tasks and useful in many NLP applications.
- Novel NLU models showcasing novel topologies and techniques.
- Simple REST API server:
- serving trained models (for inference).
- plug-in system for adding your own model.
- 4 Demos of models (pre-trained by us) showcasing NLP Architect (Dependency parser, NER, Intent Extraction, Q&A).
- Based on optimized Deep Learning frameworks:
- TensorFlow.
- Intel-Optimized TensorFlow with MKL-DNN.
- Dynet.
- Essential utilities for working with NLP models – Text/String pre-processing, IO, data-manipulation, metrics, embeddings.
- Supports CPU, GPU and Intel Optimized Tensorflow (MKL-DNN) backends.
- Supports MKL-DNN flavor of Tensorflow out of the box.
- Use NLP Architext t0:
- Train models using provided algorithms, reference datasets and configurations.
- Train models using your own data.
- Create new/extend models based on existing models or topologies.
- Explore how deep learning models tackle various NLP tasks.
- Experiment and optimize state-of-the-art deep learning algorithms.
- Integrate modules and utilities from the library to solutions.
Website: intellabs.github.io/nlp-architect
Support: Documentation, GitHub Code Repository
Developer: Intel® AI Lab – NLP Architect development team
License: Apache License 2.0
The NLP Architect is released as reference code for research purposes. It’s not an official Intel product.
The NLP Architect requires Python 3.6+. The default installation of NLP Architect use CPU-based binaries of all deep learning frameworks. Intel Optimized MKL-DNN binaries will be installed if a Linux is detected. GPU backed is supported online on Linux and if a GPU is present.
NLP Architect is written in Python. Learn Python with our recommended free books and free tutorials.
Related Software
| Python Natural Language Processing Tools | |
|---|---|
| PyTorch-Transformers | Library of state-of-the-art pre-trained models for NLP |
| NLTK | Natural Language Toolkit |
| spaCy | Industrial strength natural language processing |
| scikit-learn | Machine learning library |
| Haystack | AI orchestration framework |
| Gensim | Vector space modeling and topic modeling toolkit |
| flair | Simple framework for state-of-the-art NLP |
| TextBlob | Python (2 and 3) library for processing textual data |
| doccano | Data labelling and text annotation platform |
| BERTopic | Topic modeling |
| textacy | Python library for performing NLP tasks |
| Presidio | Data protection and de-identification SDK |
| polyglot | Multilingual text (NLP) processing toolkit |
| AllenNLP | Apache 2.0 NLP research library |
| Snips NLU | Natural Language Understanding Python library |
| PyNLPI | Various modules useful for common, and less common, NLP tasks |
| nlpnet | Natural Language Processing with neural networks |
| Pattern | Web mining module |
| GluonNLP | Deep Learning for NLP |
| PyTorch-NLP | Neural network layers, text processing modules and datasets |
| NLP Architect | Deep Learning NLP/NLU library |
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