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1,489–1,512 of 2,570 · Most stars

WeMM-Embedding is a family of universal multimodal embedding models by the WeChat Vision Team at Tencent, supporting multimodal understanding and retrieval.

  • embedding-models
  • multimodal
  • multimodal-llm

Fully async, multithreaded, predictive, open source, 3.01 reach, 1.005 timer, 0.01% speed, 99.99% antikb, "bypassable" 1.8-1.21 minecraft anticheat.

中文长文本分类、短句子分类、多标签分类、两句子相似度(Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short),字词句向量嵌入层(embeddings)和网络层(graph)构建基类,FastText,TextCNN,CharCNN,TextRNN, RCNN, DCNN, DPCNN, VDCNN, CRNN, Bert, Xlnet, Albert, Attention, DeepMoji, HAN, 胶囊网络-CapsuleNet, Transformer-encode, Seq2seq, SWEM, LEAM, TextGCN

  • text-classification
  • keras
  • rcnn
  • dcnn

NEO Emacs (WIP): GPU powered Emacs written in Rust with a modern display engine. Aiming for modern design & multi-threaded Elisp, 10x performance, zero-pause concurrent GC and 100% Emacs compatibility.

  • emacs
  • rust
  • neomacs
  • elisp

Microsoft.Recognizers.Text provides recognition and resolution of numbers, units, date/time, etc. in multiple languages (ZH, EN, FR, ES, PT, DE, IT, TR, HI, NL. Partial support for JA, KO, AR, SV). Packages available at: https://www.nuget.org/profiles/Recognizers.Text, https://www.npmjs.com/~recognizers.text