Recommended layout:
checkpoints/
omnivae/
av_vae/
state_dict.pt
generation/
t2i/
checkpoint-00495000/
transformer/
metadata.json
t2v/
checkpoint-00350000/
transformer/
metadata.json
t2a/
checkpoint-00195000/
transformer/
metadata.json
t2av/
checkpoint-00045000/
video/
audio/
bridges/
metadata.json
final/
transformer_video/
transformer_audio/
bridges/
metadata.json
Inference-only export layout:
model_ckpts/
manifest.json
t2i/
t2i_recon/
transformer/
tokenizer/
scheduler/
resolved_config.json
metadata.json
t2av/
t2av_recon_avclip/
transformer_video/
transformer_audio/
bridges/
tokenizer/
scheduler/
resolved_config.json
metadata.json
Create the inference-only packages with:
python scripts/export_inference_checkpoints.py \
--output-root /path/to/model_ckpts \
--overwriteThe export keeps only files needed for inference/evaluation. It deliberately
does not copy root-level optimizer.bin, training scheduler.bin,
random_states_*.pkl, dataloader_state_rank*.bin, .checkpoint_complete, or
the accelerator root model.safetensors. The scheduler/ directory is kept
because it is the diffusion scheduler used at inference time.
Inference and evaluation code accepts both trainer-saved checkpoint-XXXXXXXX
directories and these inference-only package directories. Inference-only
packages report checkpoint step 0 internally so downstream code does not rely
on an encoded training step.
Training recipes use these environment variables:
OMNIVAE_CKPT: shared OmniVAE checkpoint.OMNIVAE_VIDEO_CKPT: video branch override for T2AV.OMNIVAE_AUDIO_CKPT: audio branch override for T2A/T2AV.T2I_TRANSFORMER_CKPT: stage-1 transformer used to initialize T2V.T2V_TRANSFORMER_CKPT: stage-2 transformer used to initialize T2AV.T2A_TRANSFORMER_CKPT: stage-3 transformer used to initialize T2AV.
The public VAE type is omnivae; univae remains accepted only as a backward-compatible alias.