Showing 21-40 of 106 projects
A flexible and powerful parameter server for large-scale machine learning models and distributed training.
facebookresearch/metaseq is a Python library for large-scale AI and machine learning research projects.
A large-scale 7B pretraining language model developed by BaiChuan-Inc. for AI and natural language processing.
A large-scale internal network scanning tool with PowerShell and Cobalt Strike plugins, supporting various protocols and features for penetration testing.
Titan is a distributed graph database that can be used for building large-scale data-intensive applications.
An open-source Kubernetes extension that automates management of large-scale applications on Kubernetes.
This is a large-scale open-source Chinese knowledge graph dataset for AI and machine learning applications.
A high-quality, distributed vector search library for large-scale AI and machine learning applications.
A large-scale non-linear optimization library for computer vision and other scientific applications.
The Open Images dataset, a large-scale, diverse dataset of images that are annotated with object bounding boxes, visual relationships, and attributes.
A unified and scalable ML library for large-scale distributed training, model serving, and federated learning.
Large-scale, WebGL-powered geospatial data visualization and analysis engine.
SS CMS is a .NET Core-based content management system that enables developers to easily build large-scale websites with low cost and maintenance.
A fast, easy-to-use and extensible toolkit for large-scale AI model development.
Undertow is a high-performance, non-blocking web server written in Java, suitable for serving large-scale web apps.
High-level guidelines for writing maintainable, scalable CSS for large-scale projects.
A fast, open-source graph database built using GraphBLAS for use in large-scale knowledge graph applications.
A high-performance distributed training framework for Reinforcement Learning in Python
A large-scale vision-language model for video understanding and generation.
A powerful graph embedding library for generating node embeddings from large-scale graph-structured data.
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