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# https://github.com/huggingface/huggingface.jsself_forcing_from_cd
OmniMem ordinary self-forcing checkpoint initialized from CD-trained generator weights.
This release contains the generator EMA weights at self-forcing training step 600. It is the initialization checkpoint used by long_rolling_plain_from_cd.
Checkpoint lineage
CD step-4500 EMA → ordinary self-forcing step-600 EMA → plain rolling training.
Contents
config.json- Two
safetensorsweight shards and their index SHA256SUMSfor payload integrity checking
The weights retain their original FP32 storage. The model configuration uses NSA top-12 block selection.
Usage
Use compatible OmniMem code with CausalWanNSAModel and CausalWanT2VPipeline.
The Wan2.1 VAE, UMT5 text encoder, and tokenizer are separate required components.
from omnimem.models.transformers.causal_wan_nsa_model import CausalWanNSAModel
model = CausalWanNSAModel.from_pretrained(
"omnimem/self_forcing_from_cd"
)
The original checkpoint configuration is preserved unchanged. Its saved class name
records the training wrapper, and _name_or_path records the upstream CD initialization source.
The released payload is the ordinary self-forcing step-600 EMA checkpoint.
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