From 2ba60a292823ddb4c9d9b89c2597dad45f34da42 Mon Sep 17 00:00:00 2001 From: Aryan Kumar <156166681+aryan5v@users.noreply.github.com> Date: Sun, 8 Nov 2026 23:08:04 +0000 Subject: [PATCH] [docs]: point the README and news links at the canonical site host --- README.md | 32 ++++++++++++++--------------- docs-site/scripts/transfer-docs.mjs | 4 ++-- 2 files changed, 18 insertions(+), 18 deletions(-) diff --git a/README.md b/README.md index ca51193da..619a53103 100644 --- a/README.md +++ b/README.md @@ -3,23 +3,23 @@

- | Documentation | Cookbook | Quick Start | Weekly Dev Meeting | 🟣💬 Slack | 🟣💬 WeChat | + | Documentation | Cookbook | Quick Start | Weekly Dev Meeting | 🟣💬 Slack | 🟣💬 WeChat |

**FastVideo is a unified post-training and real-time inference framework for accelerated video generation.** ## Recent news -- `2026/10/21`: Release [FastH3 Omni](https://huggingface.co/FastVideo/FastVideo-FastH3-Omni-8-Step-V1) (Ref2VA): reference-conditioned video-and-audio generation from a prompt plus ordered image, video and audio references, in eight fused forwards. It runs on consumer Blackwell (RTX 5090, RTX PRO 6000, DGX Spark — [NVFP4 QAD](https://huggingface.co/FastVideo/FastH3-OmniRef-NVFP4-QAD)), on RTX 4090 (FP8) and on Apple Silicon (MLX). See the [cookbook](https://haoailab.com/FastVideo/cookbook/minimax-h3/) and the [inference guide](https://hao-ai-lab.github.io/FastVideo/inference/fasth3_omniref/). +- `2026/10/21`: Release [FastH3 Omni](https://huggingface.co/FastVideo/FastVideo-FastH3-Omni-8-Step-V1) (Ref2VA): reference-conditioned video-and-audio generation from a prompt plus ordered image, video and audio references, in eight fused forwards. It runs on consumer Blackwell (RTX 5090, RTX PRO 6000, DGX Spark — [NVFP4 QAD](https://huggingface.co/FastVideo/FastH3-OmniRef-NVFP4-QAD)), on RTX 4090 (FP8) and on Apple Silicon (MLX). See the [cookbook](https://haoailab.com/FastVideo/cookbook/minimax-h3/) and the [inference guide](https://haoailab.com/FastVideo/inference/fasth3_omniref/). - `2026/10/06`: FastVideo now supports [Kandinsky 6](https://x.com/kandinskylab_ai/status/2107374635218055345) from Kandinsky Lab: text- and image-to-video with synchronized audio (base and 10-step distilled pi-Flow checkpoints) plus video super-resolution up to 4x. See the [Kandinsky 6 recipes](https://haoailab.com/FastVideo/cookbook/kandinsky6/). - `2026/10/06`: FastH3 V2 now runs on a single consumer machine: NVIDIA RTX 5090, RTX 4090 and RTX PRO 6000 GPUs, DGX Spark and Apple Silicon. We also release [FastH3 Trim](https://huggingface.co/FastVideo/FastVideo-FastH3-Trim-8-Step-NVFP4), an experimental pruned model that is 4.2× smaller than base H3 and runs in as little as 8 GB of GPU memory. Get the [models](https://huggingface.co/collections/FastVideo/fastvideo-fasth3) and read the [Blog](https://haoailab.com/blogs/fasth3-rtx/). - `2026/09/15`: Release [FastH3 8-Step V2](https://huggingface.co/FastVideo/FastVideo-FastH3-8-Step-V2), an eight-forward data-free DMD2 checkpoint distilled from MiniMax-H3 with 80% Video Sparse Attention. Run it with `examples/inference/basic/basic_fasth3_8step.py` or the [FastH3 8-Step V2 recipe](https://haoailab.com/FastVideo/cookbook/minimax-h3/). - `2026/09/01`: FastH3 now runs locally on Apple Silicon through MLX and on NVIDIA DGX Spark through CUDA 13, including two-Spark inference. Follow the [FastH3 recipes](https://haoailab.com/FastVideo/cookbook/minimax-h3/) and read the [Blog](https://haoailab.com/blogs/fasth3-local/). - `2026/08/27`: [FastH3 Preview v1](https://haoailab.com/blogs/fasth3-preview/) is an open-weight 4-step sparse-distilled MiniMax-H3 model for synchronized video-and-audio generation, developed in collaboration with [Nuva Lab](https://nuvalab.ai/) and the [NVIDIA FastGen team](https://github.com/NVlabs/FastGen). Download the recommended [VSA / Data-Free weights](https://huggingface.co/FastVideo/FastVideo-FastH3-4-step-Preview-v1-VSA-DataFree), or see the [full FastH3 collection](https://huggingface.co/collections/FastVideo/fastvideo-fasth3). -- `2026/08/19`: FastVideo now supports MLX on Apple Silicon with [FastMetal-QAD](https://huggingface.co/collections/FastVideo/fastmetal), a family of 1.3B, 5B, and 14B models optimized for Mac. Follow the [MLX install guide](https://hao-ai-lab.github.io/FastVideo/getting_started/installation/mlx/) and read the [Blog](https://haoailab.com/blogs/fastmetal/). +- `2026/08/19`: FastVideo now supports MLX on Apple Silicon with [FastMetal-QAD](https://huggingface.co/collections/FastVideo/fastmetal), a family of 1.3B, 5B, and 14B models optimized for Mac. Follow the [MLX install guide](https://haoailab.com/FastVideo/getting_started/installation/mlx/) and read the [Blog](https://haoailab.com/blogs/fastmetal/). ### More News -- [All announcements and earlier milestones](https://hao-ai-lab.github.io/FastVideo/news/). +- [All announcements and earlier milestones](https://haoailab.com/FastVideo/news/). ## Key Features @@ -33,16 +33,16 @@ FastVideo has the following features: - [Sparse distillation](https://hao-ai-lab.github.io/blogs/fastvideo_post_training/) to achieve >50x denoising speedup - Scalable training with FSDP2, sequence parallelism, and selective activation checkpointing. - Causal distillation through Self-Forcing - - See this [page](https://hao-ai-lab.github.io/FastVideo/training/overview/) for the supported training workflows, and the [support matrix](https://hao-ai-lab.github.io/FastVideo/inference/support_matrix/) for supported models. + - See this [page](https://haoailab.com/FastVideo/training/overview/) for the supported training workflows, and the [support matrix](https://haoailab.com/FastVideo/inference/support_matrix/) for supported models. - State-of-the-art performance optimizations for inference - Sequence Parallelism for distributed inference - Multiple state-of-the-art attention backends - User-friendly CLI and Python API - - See this [page](https://hao-ai-lab.github.io/FastVideo/inference/optimizations/) for full list of supported optimizations. + - See this [page](https://haoailab.com/FastVideo/inference/optimizations/) for full list of supported optimizations. - Diverse hardware and OS support - Support H100, A100, 4090 - Support Linux, Windows, MacOS - - See this [page](https://hao-ai-lab.github.io/FastVideo/inference/support_matrix/) for full list of supported models, hardware assumptions, and optimization compatibility. + - See this [page](https://haoailab.com/FastVideo/inference/support_matrix/) for full list of supported models, hardware assumptions, and optimization compatibility. - Realtime video generation & editing - [Dreamverse](apps/dreamverse/README.md): stream and "vibe direct" video in realtime ([live demo](https://dreamverse.fastvideo.org/)), deployable on local GPU, a self-hosted B200 server, Docker, or serverless Modal @@ -58,13 +58,13 @@ source .venv/bin/activate UV_TORCH_BACKEND=cu126 uv pip install fastvideo ``` -Platform guides: [NVIDIA GPUs](https://hao-ai-lab.github.io/FastVideo/getting_started/installation/gpu/), [DGX Spark / GB10](https://hao-ai-lab.github.io/FastVideo/getting_started/installation/spark/), [Apple Silicon MLX](https://hao-ai-lab.github.io/FastVideo/getting_started/installation/mlx/), [AMD / ROCm](https://hao-ai-lab.github.io/FastVideo/getting_started/installation/amd/) — or the [full installation guide](https://hao-ai-lab.github.io/FastVideo/getting_started/installation/). +Platform guides: [NVIDIA GPUs](https://haoailab.com/FastVideo/getting_started/installation/gpu/), [DGX Spark / GB10](https://haoailab.com/FastVideo/getting_started/installation/spark/), [Apple Silicon MLX](https://haoailab.com/FastVideo/getting_started/installation/mlx/), [AMD / ROCm](https://haoailab.com/FastVideo/getting_started/installation/amd/) — or the [full installation guide](https://haoailab.com/FastVideo/getting_started/installation/). -To have a coding agent do the install, give it the [agent install prompt](https://hao-ai-lab.github.io/FastVideo/getting_started/installation/#install-with-an-ai-coding-agent). +To have a coding agent do the install, give it the [agent install prompt](https://haoailab.com/FastVideo/getting_started/installation/#install-with-an-ai-coding-agent). ## Sparse Distillation -Sparse distillation reaches >50× denoising speedup. See the [distillation guide](https://hao-ai-lab.github.io/FastVideo/distillation/dmd/) and the [blog](https://hao-ai-lab.github.io/blogs/fastvideo_post_training/); the training recipes live under [`examples/distill/`](examples/distill/) with the [FastVideo Synthetic datasets](https://huggingface.co/FastVideo). +Sparse distillation reaches >50× denoising speedup. See the [distillation guide](https://haoailab.com/FastVideo/distillation/dmd/) and the [blog](https://hao-ai-lab.github.io/blogs/fastvideo_post_training/); the training recipes live under [`examples/distill/`](examples/distill/) with the [FastVideo Synthetic datasets](https://huggingface.co/FastVideo). ## Dreamverse — Realtime Video Generation & Editing @@ -83,7 +83,7 @@ serverless [Modal](apps/dreamverse/scripts/modal/README.md) — see the ### Generating Your First Video -Here's a minimal example to generate a video using the default settings. Make sure VSA kernels are [installed](https://hao-ai-lab.github.io/FastVideo/attention/vsa/#installation). Create a file called `example.py` with the following code: +Here's a minimal example to generate a video using the default settings. Make sure VSA kernels are [installed](https://haoailab.com/FastVideo/attention/vsa/#installation). Create a file called `example.py` with the following code: ```python import os @@ -120,13 +120,13 @@ Run the script with: python example.py ``` -For a more detailed guide, please see our [inference quick start](https://hao-ai-lab.github.io/FastVideo/inference/inference_quick_start/). +For a more detailed guide, please see our [inference quick start](https://haoailab.com/FastVideo/inference/inference_quick_start/). ## More Guides -- [Design Overview](https://hao-ai-lab.github.io/FastVideo/design/overview/) -- [Distillation Guide](https://hao-ai-lab.github.io/FastVideo/distillation/dmd/) -- [Contribution Guide](https://hao-ai-lab.github.io/FastVideo/contributing/overview/) +- [Design Overview](https://haoailab.com/FastVideo/design/overview/) +- [Distillation Guide](https://haoailab.com/FastVideo/distillation/dmd/) +- [Contribution Guide](https://haoailab.com/FastVideo/contributing/overview/) ## Awesome work using FastVideo or our research projects @@ -141,7 +141,7 @@ For a more detailed guide, please see our [inference quick start](https://hao-ai ## 🤝 Contributing -We welcome all contributions. Please check out our guide [here](https://hao-ai-lab.github.io/FastVideo/contributing/overview/). +We welcome all contributions. Please check out our guide [here](https://haoailab.com/FastVideo/contributing/overview/). See details in [development roadmap](https://github.com/hao-ai-lab/FastVideo/issues/899). ## Acknowledgement diff --git a/docs-site/scripts/transfer-docs.mjs b/docs-site/scripts/transfer-docs.mjs index a3350cf98..e60808ec7 100644 --- a/docs-site/scripts/transfer-docs.mjs +++ b/docs-site/scripts/transfer-docs.mjs @@ -265,7 +265,7 @@ export async function transferDocs() { .replace(/\[([^\]]+)\]\([^)]+\)/g, "$1") .split(/:\s|\.\s/)[0] .replace(/\.$/, ""); - const href = links.at(-1)?.[2] ?? "https://hao-ai-lab.github.io/FastVideo/news/"; + const href = links.at(-1)?.[2] ?? "https://haoailab.com/FastVideo/news/"; const iso = date.replaceAll("/", "-"); const label = new Intl.DateTimeFormat("en", { month: "short", @@ -277,7 +277,7 @@ export async function transferDocs() { }); await writeFile( join(content, "_snippets/home-news.mdx"), - `
\n

Recent news

All announcements →
\n\n
\n`, + `
\n

Recent news

All announcements →
\n\n
\n`, ); await writeFile(join(content, "_snippets/home-projects.mdx"), asMdx(projects.trim())); await rm(join(content, "index.md"));