NeuronBlocks vs Stanza
Overview
🔥 Trending in Text & Language Models on StackShare
Detailed Comparison
It is a NLP deep learning modeling toolkit that helps engineers/researchers to build end-to-end pipelines for neural network model training for NLP tasks. The main goal of this toolkit is to minimize developing cost for NLP deep neural network model building, including both training and inference stages. | It is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. The toolkit is designed to be parallel among more than 70 languages, using the Universal Dependencies formalism. |
Sentence Classification; Sentiment Analysis | Native Python implementation requiring minimal efforts to set up;
Full neural network pipeline for robust text analytics, including tokenization, multi-word token (MWT) expansion, lemmatization, part-of-speech (POS) and morphological features tagging, dependency parsing, and named entity recognition;
Pretrained neural models supporting 66 (human) languages;
A stable, officially maintained Python interface to CoreNLP |
Statistics | |
GitHub Stars 1.5K | GitHub Stars 7.6K |
GitHub Forks 193 | GitHub Forks 926 |
Stacks 2 | Stacks 9 |
Followers 8 | Followers 34 |
Votes 0 | Votes 0 |
Integrations | |
| No integrations available | |
What are some alternatives to NeuronBlocks, Stanza?
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Jina
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FastText
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Flair
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Transformers
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Gensim
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Sentence Transformers
It provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various tasks.
