Displaying 1 to 15 from 15 results

Chinese-Word-Vectors - 100+ Chinese Word Vectors 上百种预训练中文词向量

  •    Python

This project provides 100+ Chinese Word Vectors (embeddings) trained with different representations (dense and sparse), context features (word, ngram, character, and more), and corpora. One can easily obtain pre-trained vectors with different properties and use them for downstream tasks. Moreover, we provide a Chinese analogical reasoning dataset CA8 and an evaluation toolkit for users to evaluate the quality of their word vectors.

Milvus - An open-source vector database for embedding similarity search and AI applications

  •    Go

Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment. Milvus 2.0 is a cloud-native vector database with storage and computation separated by design. All components in this refactored version of Milvus are stateless to enhance elasticity and flexibility.

pymde - Minimum-distortion embedding with PyTorch

  •    Python

The official documentation for PyMDE is available at www.pymde.org. This repository accompanies the monograph Minimum-Distortion Embedding.

word2vec - Go library for performing computations in word2vec binary models

  •    Go

word2vec is a Go package which provides functions for querying word2vec models (see https://code.google.com/p/word2vec). Any binary word2vec model file can be loaded and queried. If you haven't setup Go before, you need to first set a GOPATH (see https://golang.org/doc/code.html#GOPATH).

implant - Simple utility for embedding files/resources inside golang binaries

  •    Go

implant is a simple utility which allows data to be embedded directly in golang applications (implant is a synonym of embed). The expected use-case is that you have a HTTP-server, or similar golang application which you wish to distribute as a single binary but which needs some template files, HTML files, or other media.

unfurl - Scraper for oEmbed, Twitter Cards and Open Graph metadata - fast and Promise-based :zap:

  •    TypeScript

Unfurl (spread out from a furled state) will take a url and some options, fetch the url, extract the metadata we care about and format the result in a saine way. It supports all major metadata providers and expanding it to work for any others should be trivial. So you know when you link to something on Slack, or Facebook, or Twitter - they typically show a preview of the link. To do so they have crawled the linked website for metadata and enriched the link by providing more context about it. Which usually entails grabbing its title, description and image/player embed.

ember - Embed arbitrary resources into a go executable at runtime, after the executable has been built

  •    Go

Ember is a lightweight library and tool for embedding arbitrary resources into a go executable at runtime. The resources don't need to exist at compile time. Embedding binary files (eg. zip-archives and executables) is supported.

fetch-base64 - A node package to fetch local or remote files in base64 encoding.

  •    Javascript

A node package to fetch local or remote files in base64 encoding. Useful for inlining assets (images, web fonts, etc.) into HTML or CSS documents. Disclaimer: I've only used this for images so far, but there is no reason why it shouldn't work for any other kind of files.

exembed - Go Embed experiments

  •    Go

See accompanying blog post at https://blog.carlmjohnson.net/post/2021/how-to-use-go-embed/.

file2go - Dead-simple file embedding tool for Go

  •    Go

Dead-simple file embedding tool for Go similar to file2c. Deprecated by embed package.

monobind - C++ binder for mono runtime

  •    C++

monobind is a lightweight header-only library that exposes C++ types in C# and vice versa, mainly to create C# bindings of existing C++ code. It is inspired by the excellent library Boost.Python and tries to achieve simular goals of minimizing boilerplate code when implementing interoperability between C++ and C#. monobind requires at least C++14 compatible compiler to run. It only depends on mono - cross-platform .NET framework. You do not have to build it - simply install it from the official website to your system.

ngraph.hde - High dimensional embedding of a graph and its layout

  •    Javascript

This package implements high dimensional graph layout with O(m*(|V| + |E|)) time complexity. While the layout doesn't necessary look appealing for all possible graphs, this package provides amazing initial configuration for nodes for subsequent refinement by ngraph.forcelayout or d3-force.

amazon-denseclus - Clustering for mixed-type data

  •    Jupyter

DenseClus is a Python module for clustering mixed type data using UMAP and HDBSCAN. Allowing for both categorical and numerical data, DenseClus makes it possible to incorporate all features in clustering. A hands-on example with an overview of how to use is currently available in the form of a Jupyter Notebook.

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