(hiddensize=[768, 2048], depth=[28, 6]) over a 64-channel geometry-native latent, at 672×378 and V=81, with metric Plücker camera conditioning and Qwen3-0.6B text. This repo is self-contained for GAE-64 inference: codec, per-channel latent statistics, DA3 feature-level stats, and the flow transformer. The frozen DA3-GIANT encoder / DPT head comes from Or, after the files are in ckpts/: Image-to-video uses 50 Euler steps and CFG 2 with one reference view. - codec/ — safetensors + config.json - gae64.pt — drop-in checkpoint for gae.loadcodec - latentstatsgae64.pt — per-channel latent mean/std - da3statsgiant5ds.tar — DA3 feature-level normalization stats - transformer/ — flow safetensors +…
Open weights
pytorch
Self-contained weights for WorldCrafter Fast image-to-video, text-to-video, and the interactive image-to-video demo. Use the WorldCrafter inference code and its pinned uv environment. The two transformer branches have independent DMD LoRA and camera adapters. The RepEncoder, text encoder, tokenizer, VAE, and scheduler are included here. No WorldCrafter-Base files are needed for Fast inference. Image-to-video uses five high-noise steps and one low-noise step per chunk. Text-to-video uses four high-noise and eight low-noise steps for the first chunk, then two high-noise and four low-noise steps. Compilation is optional with --enable-compile. inferenceconfig.json resolves shared components…
Open weights
diffusers
Base transformer weights and their matching camera adapter and LoRA for the WorldCrafter inference code. Place this directory beside WorldCrafter-Fast. Base reads the following shared folders from Fast: repencoder/, textencoder/, tokenizer/, vae/, and scheduler/. Base does not need Fast's transformer or adapter folders. The relative path is configured in inferenceconfig.json. Keep the Base-specific transformer/ and adapter/ together. SHA256SUMS covers the packaged Base files; shared component hashes are recorded in Fast's package.
Open weights
14.3B parameters
diffusers
