Tools tagged with "Distributed execution"

StyleGAN3 is NVIDIA's local AI image generation and training software for researchers and developers. Its architecture addresses generated detail that stays fixed to pixel positions instead of following the depicted objects as they move.

Optuna is a Python framework for machine learning developers and researchers who want to automate the search for model settings. Its search spaces can change with the choices made during a trial, so it can compare model architectures or classifiers as well as tune individual parameters. It's open source under the MIT license and can run on your own hardware as part of a Python workload.

Dask-ML is a Python machine learning library for people whose datasets exceed RAM or whose training and evaluation jobs take too long. It uses Dask to distribute work across a cluster of machines, while keeping interfaces familiar to users of Scikit-Learn, NumPy, and pandas. It's open source under the BSD-3-Clause license.

local-transcriber is a free, open-source app for turning audio and video recordings into text on your own computer. It's aimed at people handling private interviews, client calls or long talks who want transcription without uploading recordings to a cloud service. It runs fully offline once the required models are downloaded.

FATE is a self-hosted federated learning framework for enterprises and institutions that want to train models together while protecting data privacy. It supports collaboration across participating organizations and uses homomorphic encryption and multi-party computation (MPC) for secure computation.

ColBERT is a self-hosted neural search library for developers building document search or retrieval for AI applications. It finds relevant passages in your own text collections and stores their search representations on disk. The Python project is open source under the MIT license.

CubeSandbox is a self-hosted sandbox service for teams that need AI agents to execute code on their own infrastructure. Each sandbox has its own operating system kernel inside a hardware-isolated MicroVM.

AgentScope is a Python framework for developers building AI agent applications on their own servers. It includes an SDK, a FastAPI backend and a web UI for applications with multiple users and separate sessions.

HunyuanCustom generates videos of specific people or objects for creators and researchers who need subjects to stay recognizable across frames. It builds on HunyuanVideo and supports generation on your own hardware.

MOSS is a conversational language model from Fudan University for developers and researchers who want to run and adapt a local LLM. It includes model weights, dialogue datasets and fine-tuning code.

APPFL is an MIT-licensed Python framework for researchers and data scientists who want to train machine learning models across distributed clients while keeping training data decentralized. It supports user-defined models and lets teams test privacy-preserving federated learning methods in simulations or real distributed experiments.

TorchMD-NET is an open-source Python library for researchers who train neural network potentials for molecular dynamics. It exposes its models as PyTorch modules and connects them to GPU-accelerated simulation software, including ACEMD, OpenMM and TorchMD. It's available under the MIT license.

AgentENV runs isolated environments for AI agents across your own servers. It's for teams building parallel agent workflows or reinforcement learning systems that need many separate sandboxes.

exo is a local LLM runner for people who want to run models too large for a single machine's memory. It joins devices into a cluster and runs inference on your own hardware.

Transformer Engine is a library for developers building and running Transformer models on NVIDIA GPUs. It reduces compute and memory demands in training and inference through low-precision arithmetic and optimized model components.

Fish Diffusion is a Python framework for developers and researchers training diffusion models for text-to-speech, singing voice synthesis and singing voice conversion. It works with your own datasets and provides code you can adapt for different voice generation tasks.

ms-swift is a Python framework for developers and researchers training and deploying language and multimodal models on their own hardware. It covers model adaptation through evaluation and serving, with support for Qwen3, DeepSeek-R1, Llama4, Mistral, Qwen3-VL and InternVL3.5.

Flash Linear Attention is a Python library for researchers and developers building language models on their own hardware. It supplies reusable components for exploring linear attention, sparse attention and state space architectures.

GLiNER is a Python framework for extracting named entities from text using small models that run locally on CPUs and consumer hardware. It's for developers building document processing, personal data detection or search systems who need to choose their own entity types without training a model for each task.

NeMo Curator is an open source Python toolkit for ML engineers and data teams preparing AI training datasets. It provides repeatable curation pipelines that can run on a laptop or across a multi-node Ray cluster.

DwarfStar is a local LLM inference engine for people who want to run large DeepSeek, GLM and Qwen models on their own computers or servers. It focuses on selected models and hardware setups, and requires the project's own GGUF files rather than accepting arbitrary GGUF downloads.

AgentField is a self-hosted AI agent platform for developers building services that need to coordinate tasks under shared access rules. It combines execution, identity and audit records in infrastructure you control.

NeMo RL is NVIDIA's Python library for researchers and engineering teams adapting language and multimodal models on their own hardware. It supports experiments on a GPU workstation and distributed training across multiple nodes.

FlashInfer is a GPU kernel library for developers building LLM inference systems on their own hardware or servers. It supplies the attention, matrix multiplication and mixture-of-experts operations used by model serving software.

MaxText is an LLM training library for researchers and engineers building models from scratch or adapting existing ones. It provides a reference implementation teams can modify for their own model designs, with training that scales from a single host to large clusters.

OpenCompass is an LLM evaluation framework for researchers and developers comparing models for their applications. It lets you assess models on your own hardware alongside cloud APIs in the same experiment.

Vearch is a self-hosted, distributed vector database for developers building AI applications that search embedding vectors. It combines similarity search with filters on stored fields, so an application can retrieve related content while applying criteria beyond vector similarity. It's open source under Apache 2.0 and can run on your servers through Docker, Docker Compose, or Kubernetes.

NeuralForecast is an open-source Python library for data scientists and developers who want to train and compare neural time series forecasting models in their own Python environment. It brings recurrent networks and forecasting-specific architectures under one interface, so comparing models doesn't require working with separate research implementations. The license is Apache 2.0.

torchtitan is a training platform for researchers and developers experimenting with generative AI models on their own GPU servers or clusters. Its replaceable components and extension points support work on model architectures and training infrastructure.

MLX LM is a Python package for developers and researchers who want to generate text and adapt language models on Apple Silicon Macs. It uses MLX for local inference and training, with access through Python or a terminal.

SkyRL is a Python library for researchers and developers who want to train LLMs with reinforcement learning on their own hardware. Its Tinker API support lets you run existing Tinker training scripts against a server you control without changing the scripts. It's open source under Apache 2.0.

taOS is a self-hosted AI agent platform for people who want to run assistants on their own computers and keep their conversations, files, and memory there. It brings agent management and local model access into a browser-based desktop.

CleanRL is a Python deep reinforcement learning library for researchers and developers who want to study or modify an algorithm without tracing it through a large modular codebase. Each algorithm variant lives in one standalone file. Experiments can run locally, while Docker and AWS integration support cloud execution through AWS Batch.

MiniMind is a toolkit for learners and developers who want to understand language models by training small ones on their own hardware. Its core training algorithms use native PyTorch code that you can inspect and change.