Inference Pipeline With Iterative Denoising And Step Wise Guidance Application

via “multi-model ensemble inference with guidance techniques”

🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.

Unique: Implements Perturbed Attention Guidance (PAG) by modifying attention maps during inference, scaling attention weights based on spatial or semantic features without retraining. PAG operates by computing attention perturbations and blending them with original attention, enabling dynamic quality tuning. This is more efficient than retraining and enables real-time quality adjustment via guidance parameters.

More efficient than retraining because guidance techniques modify attention maps at inference time, adding only 10-20% latency. Outperforms post-processing because guidance operates during generation, enabling the model to adjust its predictions based on attention feedback.