基于Pytorch和torchtext的自然语言处理深度学习框架。

NLP 领域常见任务的实现，包括新词发现、以及基于pytorch的词向量、中文文本分类、实体识别、摘要文本生成、句子相似度判断、三元组抽取、预训练模型等。

🐍 Python Implementation and Extension of RDF2Vec

word2vec implementation for skip-gram in pytorch

PyTorch implementation of the Word2Vec (Skip-Gram Model) and visualizing the trained embeddings using TSNE

Romanian Word Embeddings. Here you can find pre-trained corpora of word embeddings. Current methods: CBOW, Skip-Gram, Fast-Text (from Gensim library). The .vec and .model files are available for download (all in one archive).

A lock-free, in-memory fuzzy search engine for Kotlin Multiplatform. L2-normalized sparse vector embeddings with O(1) cosine similarity — handles typos, transpositions, and blind continuation. Zero-allocation search via primitive arrays, reactive StateFlow results, and instant cold-start via JSONL import/export.

意味表現学習

(EPJ DS) Time-varying graph representation learning via higher-order skip-gram with negative sampling

Training Model with converting words to vector and Skip-Gram

Skipgram with Hierarchical Softmax

Word2Vec sikp-gram model with negative sampling implementation with python3

An embedding-based approach for cross-site account correlation

An implementation of word2vec skip-gram algorithm

This repository contains what I'm learning about NLP

For all your n-gram and skip-gram needs 🔠

My solutions to the class assignments

Social trust Network Embedding (ICDM 2019)

gdp is generating distributed representation code sets written by pytorch. This code sets is including skip gram and cbow.

Word2Vec Skip-Gram model implementation using TensorFlow 2.0 to learn word embeddings from a small Wikipedia dataset (text8). Includes training, evaluation, and cosine similarity-based nearest neighbors