PyTorch-NLP, or torchnlp for short, is a library of neural network layers, text processing modules and datasets designed to accelerate Natural Language Processing (NLP) research.
It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping.
PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. PyTorch-NLP also provides neural network modules and metrics.
The software is released under an open source license.
Packages:
- torchnlp.datasets – introduces modules capable of downloading, caching and loading commonly used NLP datasets.
- torchnlp.word_to_vector – introduces multiple pretrained word vectors. The package handles downloading, caching, loading, and lookup.
- torchnlp.nn – introduces a set of torch.nn.Module commonly used in NLP.
- torchnlp.encoders – supports encoding objects as a vector torch.Tensor and decoding a vector torch.Tensor back.
- torchnlp.samplers – introduces a set of samplers. Samplers sample elements from a dataset. torchnlp.samplers plug into torch.utils.data.distributed.DistributedSampler and torch.utils.data.DataLoader.
- torchnlp.metrics – introduces a set of modules able to compute common NLP metrics.
- torchnlp.utils – contains any other module or object that is useful in building out a NLP pipeline.
- torchnlp.download – contains modules useful for donwload and extracting datasets.
Website: github.com/PetrochukM/PyTorch-NLP
Support: Documentation
Developer: Michael Petrochuk and contributors
License: BSD 3-Clause “New” or “Revised” License
PyTorch-NLP 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 |
Read our verdict in the software roundup.
 LinuxLinks helps you discover the best free and open source software for Linux. Explore our extensive collection of recommended applications, including alternatives to popular proprietary software.We also publish software reviews, Linux tutorials, hardware reviews, free programming books and articles covering the wider open source community. Browse our Linux resources to discover more. Know a useful free and open source Linux application we haven't covered? Suggest a program for inclusion. Has your software been featured on LinuxLinks? Display one of our Featured on LinuxLinks badges on your website or GitHub README. |
Please read our Comment Policy before commenting.