tdrussell/diffusion-pipe

Health v2 · maintenance only

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Adoption not part of the score

2015 stars · 285 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python training script for fine-tuning diffusion models (image and video generation) using DeepSpeed pipeline parallelism across multiple GPUs. It supports many popular models like SDXL, Flux, Wan, and HunyuanVideo with latent caching, checkpointing, and Tensorboard metrics.

Use cases

• train a LoRA for Flux or SDXL on multiple GPUs
• fine-tune a video diffusion model like Wan2.1 or HunyuanVideo
• train a diffusion model too large to fit on a single GPU
• precompute latents and text embeddings for faster diffusion training
• resume diffusion model training from a checkpoint
• evaluate generalization of a fine-tuned diffusion model on a held-out set

When to choose

• you want to fine-tune or train LoRAs for supported image/video diffusion models
• you need pipeline parallelism to train models larger than one GPU's memory
• you want efficient multi-GPU latent and text embedding caching
• you run Linux with NVIDIA GPUs and DeepSpeed

When to avoid

• you need native Windows training - DeepSpeed support is partial
• you want a GUI-based trainer rather than TOML-configured CLI scripts
• your model is not among the supported architectures and you don't want to implement a subclass

Facets

cli-tool · maturity active

llm-training deep-learning machine-learning gpu-computing deep-learning machine-learning image-processing artificial-intelligence python cli diffusion-models pipeline-parallelism lora-training deepspeed fine-tuning stable-diffusion flux video-generation text-to-image tensorboard video linux gpu

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For agents

markdown · JSON · MCP: product_card(name="tdrussell/diffusion-pipe")