license: apache-2.0
base_model: Wan-AI/Wan2.1-I2V-14B-720P
library_name: diffsynth
pipeline_tag: image-to-video
tags:
- image-to-video
- camera-control
- video-generation
- wan
WorldCast — anchor-conditioned camera-control video generation
Trained external modules (a source self-attention bank + anchor channel
adapter + camera projection, ~2 GB) that attach to a frozen
Wan2.1-I2V-14B-720P backbone, enabling anchor-viewpoint-conditioned video
generation along explicit camera trajectories — orbit_360 (full orbit
ring), orbit_<N>[_cw|_ccw] (horizontal arcs of any sweep),
orbit_180_push / orbit_360_push (push-pull arcs), lemniscate
(figure-8), orbit_tilt_20
(tilted orbit ring), spiral (SEVA 2-turn spiral), zoom_in / zoom_out
(dolly), turn_left /
turn_right (lateral trucks) — with Plücker camera-ray injection
and first-frame/body-view anchor conditioning.
Files
⚠️ Weights: coming soon. The checkpoints listed below are not published yet — they will be added to this repository in an upcoming update.
| File | What it is |
|---|---|
checkpoints/worldcast_bank.safetensors |
the trained modules (source_self_attn_bank.* + anchor_channel_adapter.*), bank-only — the base DiT weights are NOT inside |
checkpoints/base_dit.safetensors |
the frozen base the bank was trained against (DiT-compatible weights + camera_proj + I2V channel adapter) — the two checkpoints must come from the same release |
Requirements
- Code: the companion inference repository (WorldCast) — inference only, no training code
- Base model: Wan-AI/Wan2.1-I2V-14B-720P (VAE / text-image encoders come from the base model tree)
- GPU: >= 48 GB VRAM recommended for 480x832, 81 frames
Quickstart
git clone <worldcast-repo-url> worldcast && cd worldcast
pip install -r requirements.txt
# place weights
mkdir -p checkpoints pretrained
cp worldcast_bank.safetensors checkpoints/
cp base_dit.safetensors checkpoints/
# download the Wan2.1 base into pretrained/Wan2.1-I2V-14B-720P/
python demo.py \
--manifest demo_case_traj5.json \
--model_root pretrained/Wan2.1-I2V-14B-720P \
--ckpt checkpoints/worldcast_bank.safetensors \
--init_dit_from checkpoints/base_dit.safetensors
Sampling defaults
50 steps / cfg 5.0 without a step-distillation LoRA; the bank is architecture-locked to the training line's flags (per-layer proj_out bank on DiT rope, 20 bank layers) — see the companion repository's README for the full flag matrix.
License
Apache-2.0 (the Wan2.1 base is Apache-2.0; these derived weights are released under the same terms).