echostyle

The six-H200 full-corpus run is in progress. Its rolling latest checkpoint is in a mutable Storage Bucket, with the verified step recorded in latest.json. The final weights will be published in this model repository. Live training and held-out validation metrics are updated throughout the run. The model initializes from OpenWAM-α at revision 52df4e66c82c5c8b480adcc8d01f4db7415dfb56. Its Slither adapter replaces the 80-dimensional robot action head with three outputs: cosine and sine of estimated mouse angle, and binary boost. It removes robot proprioception and uses fixed empty-prompt conditioning. Each example uses 33 frames at 30 Hz and 32 transition actions; the nine video frames are…

Model · Video to video

Matrix-Game-4.0

Skywork

Scene-specialized causal video renderers for Medieval Castle, Ancient Egypt, and City Racing. An executable game determines gameplay, physics and input, while the model re-renders clean low-poly RGB. HUD and sound remain separate, frame-aligned presentation layers. Each scene checkpoint has 5,001,016,512 BF16 parameters. The weights require the Matrix-Game 4.0 inference source; they are not drop-in Diffusers pipelines. Training code and training data are not included. Shared encoders/codecs are installed once for all scenes. See game asset details. Use the source release's manifest downloader with a pinned Hub commit revision and --repo-id Skywork/Matrix-Game-4.0 --repo-type model for both…

Model · Video to video

SwiftVR

H-oliday

SwiftVR is a streaming one-step generative video restoration (VR) framework presented in SwiftVR: Real-Time One-Step Generative Video Restoration. - [2026/06] Release the inference code and pretrained weights LightX2V brings faster inference and lower GPU memory usage to SwiftVR (1.91× speedup and 65.71% lower peak GPU memory per request on a single H100). It also supports multi-GPU acceleration. Ready-to-use scripts cover image and video super-resolution, offline inference, and API serving. Get started with LightX2V → - Mask-free shifted-window self-attention (MFSWA). Each spatial window is pre-gathered into a dense tensor, so every attention call reduces to a single standard…

Model · Video to video

Viggle-Animate

Viggle AI

Built on MiniMaxAI/MiniMax-H3 this repository. The cast of a two-minute music video replaced through its fast cuts, from at most one repainted frame per shot. AI-generated parody: the people shown did not take part in, approve or endorse it. Viggle-Animate replaces the character in a video with whatever you paint into one of its own frames — motion, camera and timing untouched. You prepare that one frame in an image editor; from there the video stage runs no pose estimator, segmenter, face tracker or text encoder. Two inputs, three forward passes, 26 seconds a shot on one GPU. It is strongest where replacement is hardest: fast motion, and pose transfer accurate enough to follow it. Whipping…