TrackWan 1.3B — bidirectional I2V + point-track (merged-bias, ckpt-4800)
A track-conditioned finetune of Wan2.1-Fun-1.3B (InP) for image-to-video generation
with MotionStream-style point-track motion control. This is the merged_bias bidirectional
training run, checkpoint 4800.
- Base model:
Wan-AI/Wan2.1-Fun-1.3B-InP(Apache-2.0) - What's trained here: the WanTransformer3DModel with the added track-conditioning head
(
transformer/model.safetensors, ~2.9 GB). Text encoder / VAE are the standard Wan components. - Type: research checkpoint.
⚠️ Requires FastVideo (custom architecture)
This is not a vanilla diffusers pipeline — the track-conditioning is a custom WanTrack
architecture. Load it with the FastVideo fork that produced it, e.g.:
# in the FastVideo repo, using the trackwan inference helper
import data_pipeline.trackwan_infer as twi
model, cfg = twi.load_trackwan("<this repo checked out>", "<train yaml>")
Pair it with the base Wan2.1-Fun-1.3B-InP text encoder + VAE. See the FastVideo project for the exact config/YAML and track-conditioning input format (per-frame point tracks + visibility).
Files
model.safetensors— trained transformer weights (bf16).config.json— transformer architecture config.
License
Apache-2.0, inherited from the Wan base model.