NVIDIA and Hugging Face streamline diffusion model fine-tuning

NVIDIA and Hugging Face have collaborated to integrate NVIDIA's NeMo Automodel library with Hugging Face's 🤗 Diffusers library. This integration allows for the efficient, large-scale fine-tuning of diffusion models, including text-to-image and text-to-video models, directly from the Hugging Face Hub. The system supports various parallelism strategies and parameter-efficient fine-tuning methods like LoRA, enabling users to train models without checkpoint conversion and with minimal code changes. AI

IMPACT Streamlines the process for researchers and developers to fine-tune diffusion models, potentially accelerating open-source development and adoption.

RANK_REASON Integration of two existing libraries to improve a specific workflow.

Read on Hugging Face Blog →

• 🤗 Diffusers
• DTensor
• FLUX.1-dev
• FSDP2
• Hugging Face
• HunyuanVideo
• NeMo Automodel
• NVIDIA
• PyTorch
• Wan 2.1
• WanPipeline
• WanTransformer3DModel

• infra
• product

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