lexvec
Word Embedding Model
An implementation of a word embedding model that uses character n-grams and achieves state-of-the-art results in multiple NLP tasks
This is an implementation of the LexVec word embedding model (similar to word2vec and GloVe) that achieves state of the art results in multiple NLP tasks
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81 forks
Language: Go
last commit: almost 4 years ago Related projects:
Repository | Description | Stars |
---|---|---|
vefstathiou/so_word2vec | This is a word embedding model trained on Stack Overflow posts for use in natural language processing tasks. | 40 |
tca19/dict2vec | A framework to learn word embeddings using lexical dictionaries | 115 |
cod3licious/conec | A library for training and evaluating a type of word embedding model that extends the original Word2Vec algorithm | 20 |
auspicious3000/contentvec | An implementation of a self-supervised speech representation model using PyTorch and disentangled speaker embeddings | 470 |
bakrianoo/aravec | Provides pre-trained word embedding models for Arabic text analysis | 395 |
zhangxiann/skip-gram | A Python implementation of a neural network model for learning word embeddings from text data | 6 |
hassygo/charngram2vec | A repository providing a re-implementation of character n-gram embeddings for pre-training in natural language processing tasks | 23 |
danieldk/go2vec | A package for reading and analyzing word embeddings from the word2vec format in Go. | 56 |
zhezhaoa/ngram2vec | A toolkit for learning high-quality word and text representations from ngram co-occurrence statistics | 846 |
jwieting/acl2017 | A codebase for training and using models of sentence embeddings. | 33 |
rguthrie3/morphologicalpriorsforwordembeddings | A project implementing a method to incorporate morphological information into word embeddings using a neural network model | 52 |
malllabiisc/wordgcn | A deep learning model that generates word embeddings by predicting words based on their dependency context | 290 |
fanglanting/skip-gram-pytorch | A PyTorch implementation of the skip-gram model for learning word embeddings. | 188 |
mnqu/pte | An implementation of the Predictive Text Embedding model for learning word representations from large-scale heterogeneous text networks. | 96 |
vzhong/embeddings | Provides fast and efficient word embeddings for natural language processing. | 223 |