Optimizing Bark TTS with Hugging Face Transformers: Better Transformer & Flash Attention

AI Impact Summary

The Bark TTS workflow can now be accelerated using Hugging Face Transformers optimization tooling, applying Optimum, Accelerate, and Better Transformer to Bark and its submodels. It highlights one-line export to Better Transformer and the use of Flash Attention to shrink memory and speed up inference with minimal code changes. Baseline Bark-small demonstrates ~9.38s latency and ~1.91 GB peak memory; optimized with Better Transformer and related techniques, latency drops to ~5.43s with a similar memory footprint, illustrating substantial throughput gains for real-time or batch Bark generation. Producers should ensure CUDA-enabled GPUs and compatible Bark checkpoints (suno/bark-small or suno/bark) are in use and be prepared to benchmark in their specific deployment to validate gains.