NVIDIA-NeMo在GitHub上拥有多个公共仓库,主要使用Python和Jupyter Notebook语言。其重要项目包括NeMo,一个用于大语言模型和多模态AI的生成式AI框架,以及Guardrails,一个为对话系统添加可编程保护机制的开源工具包。这些仓库为研究人员和开发人员提供了丰富的资源。
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
🎨 NeMo Data Designer: Generate high-quality synthetic data from scratch or from seed data.
Scalable toolkit for efficient model reinforcement
Scalable data pre processing and curation toolkit for LLMs
Developer Asset Hub for NVIDIA Nemotron — A one-stop resource for training recipes, usage cookbooks, datasets, and full end-to-end reference examples to build with Nemotron models
Evaluate and improve models and agents using environments
A project to improve skills of large language models
Training library for Megatron-based models with bidirectional Hugging Face conversion capability
🚀 Pytorch Distributed native training library for LLMs/VLMs with OOTB Hugging Face support
Agentic RL on Any Harness at Scale
Open-source library for scalable, reproducible evaluation of AI models and benchmarks.
A tool to configure, launch and manage your machine learning experiments.
此仓库未提供描述。
🕵️ NeMo Anonymizer: Detect and protect PII through context-aware replacement and rewriting
State-of-the-art framework for fast, large-scale training and inference of diffusion models
Make the agents you ship faster, more accurate, and safer.
A library for exporting models including NeMo and Hugging Face to optimized inference backends, and deploying them for efficient querying
:shield: NeMo Safe Synthesizer: Create private, safe versions of sensitive tabular datasets.
CI/CD templates for NeMo-FW libraries
🔌 🎨 NeMo Data Designer Plugins
NeMo SDG-PGMs is a user-friendly Python library for building probabilistic graphical models (PGMs) to generate synthetic data
此仓库未提供描述。
NVIDIA-NeMo在GitHub上构建了多个项目,涵盖生成式AI、对话系统和数据处理等领域。主要仓库包括NeMo、Guardrails和DataDesigner,旨在支持大型语言模型的开发和应用。
NVIDIA-NeMo主要使用Python和Jupyter Notebook作为其开发语言。这些语言为其公开仓库中的多个项目提供了技术基础,适用于AI和机器学习相关的应用。
是的,NVIDIA-NeMo的仓库是公开的,任何人都可以访问和使用。这种公开性促进了社区的协作和知识共享,尤其是在AI和数据处理领域。