基于Pytorch和torchtext的自然语言处理深度学习框架。
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Updated
Dec 14, 2020 - Python
基于Pytorch和torchtext的自然语言处理深度学习框架。
🎯 Task-oriented embedding tuning for BERT, CLIP, etc.
Extremely simple and fast word2vec implementation with Negative Sampling + Sub-sampling
Reinforced Negative Sampling over Knowledge Graph for Recommendation, WWW2020
MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems, KDD2021
Implements various negative sampling techniques for learning knowledge graph embeddings
SimXNS is a research project for information retrieval. This repo contains official implementations by MSRA NLC team.
⚡️ Implementation of TRON: Transformer Recommender using Optimized Negative-sampling, accepted at ACM RecSys 2023.
A PyTorch Implementation of the Skipgram Negative Sampling Word2Vec Model as Described in Mikolov et al.
Embedding模型代码和学习笔记总结
[Paper][LREC-COLING 2024] Unleashing the Power of Imbalanced Modality Information for Multi-modal Knowledge Graph Completion
[Paper][IJCNN2023] Modality-Aware Negative Sampling for Multi-modal Knowledge Graph Embedding
Treat Different Negatives Differently: Enriching Loss Functions with Domain and Range Constraints for Link Prediction
PyTorch implementation for " Conditional Negative Sampling for Contrastive Learning of Visual Representations" (https://arxiv.org/abs/2010.02037).
Some demo word2vec models implemented with pytorch, including Continuous-Bag-Of-Words / Skip-Gram with Hierarchical-Softmax / Negative-Sampling.
CBOW, Skip-gram with nagative sampling - Pytorch
gdp is generating distributed representation code sets written by pytorch. This code sets is including skip gram and cbow.
SkipGram NegativeSampling implemented in PyTorch.
Cooperation of Retriever and Ranker Framework.
北京大数据技能大赛
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