AIAny
AI Train2024
Icon for item

FastVideo

Accelerates video generation with a unified framework for inference, finetuning, LoRA, distillation, sparse attention, and distributed execution for research and demos.

Introduction

Video generation is bottlenecked by latency, memory, and training cost as much as imagination. FastVideo focuses on making inference and post-training fast enough for iteration.

What Sets It Apart

It combines finetuning, LoRA, preprocessing, distillation, sparse attention, sequence parallelism, and multiple attention backends in one stack. Speed-oriented engineering around open video DiTs helps teams move from single-GPU demos to larger experiments.

Who Should Use It

Great fit if you research or deploy open video-generation models and need faster inference plus post-training control. Look elsewhere if you want a simple creative UI.

Information

  • Websitegithub.com
  • OrganizationsHao AI Lab
  • AuthorsThe FastVideo Team, hao-ai-lab
  • Published date2024/04/24

More Items

GitHub
AI Infra2025

Measures generative AI inference performance with token-level metrics (TTFT, inter-token latency), latency, and throughput under realistic traffic patterns. Provides a multiprocess engine, real-time TUI dashboard, extensible plugins, and integrations for telemetry and result uploads, aimed at inference benchmarking and capacity planning.

GitHub
AI Train2019

Train and experiment with multi-billion to trillion-parameter transformer models on large GPU clusters using GPU-optimized building blocks and reference training scripts; offers advanced parallelism and mixed-precision support for research teams and ML engineers.

GitHub

Indexes full text of visited web pages and local files on a self‑hosted server so you can search your personal knowledge from a web UI, terminal, CLI, or an AI assistant. Runs without mandatory telemetry, offers a browser extension for automatic capture, and supports optional semantic search via a configurable embeddings endpoint.