Fine-tune video and image models at scale with NVIDIA NeMo Automodel and 🤗 Diffusers
Hugging Face Blog ● Covered by 2 sources
NVIDIA and Hugging Face integrated NVIDIA's NeMo Automodel library with the Diffusers library, enabling scalable fine-tuning of diffusion models for image and video generation directly from the Hugging Face Hub without checkpoint conversion. The integration supports flow-matching models including FLUX.1-dev, Qwen-Image, Wan 2.1, HunyuanVideo, and others, with performance benchmarks showing FLUX.1-dev achieving 35.51 images per second for full fine-tuning and 53.73 images per second for LoRA on 8 H100 GPUs. Users can now fine-tune diffusion models at any scale using YAML configurations and parameter-efficient methods like LoRA, with fine-tuned checkpoints loading directly into Diffusers pipelines for inference or sharing.
