| --- |
| 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. |
|
|
| ## ⚠️ Note on model versions |
|
|
| **A version trained on a more diverse set of camera trajectories, |
| offering improved trajectory stability and support for a wider range of |
| camera motions, is currently undergoing internal review and is not yet |
| available for public release.** We will provide updates as soon as |
| further information becomes available. |
|
|
| ## Files |
|
|
| | 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](https://huggingface.co/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 |
|
|
| ```bash |
| 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). |
| |
