NVIDIA and Hugging Face integrated NeMo Automodel to train any Diffusers-format model with FSDP2, tensor, and pipeline parallelism via YAML config—no checkpoint conversion or model rewrites required.
Summary
Developers can now fine-tune large diffusion models (FLUX.1-dev 12B, HunyuanVideo 13B) at scale without custom training pipelines or format conversions. Fine-tuned checkpoints round-trip directly back into Diffusers for inference and deployment.
Why it matters
Developers can now fine-tune large diffusion models (FLUX.1-dev 12B, HunyuanVideo 13B) at scale without custom training pipelines or format conversions. Fine-tuned checkpoints round-trip directly back into Diffusers for inference and deployment.
Implementation verdict
Replaces custom training scripts for Diffusers models. Requires PyTorch DTensor, CUDA dependencies (Docker container provided), and YAML-based configuration. Ready now—includes recipes for FLUX.1-dev, FLUX.2-dev, Wan 2.1/2.2, HunyuanVideo, Qwen-Image. Start with `pip3 install nemo-automodel` or use provided Docker image.
Sources
Dev Signal
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