Real-time audio models for speech recognition and transcription often struggle to process continuous data without delays. High data volumes cause slow inference and latency, disrupting applications like voice assistants and live transcription.
This is where Pruna comes into play.
Pruna addresses these challenges by compressing audio models to boost processing speed and maintain accuracy, ensuring smooth real-time performance even under demanding conditions.
The Preferred Smashing Methods
Batching And Compilation
For audio use cases, batching and compilation are the
preferred methods for optimizing smooth real-time tasks.
By using Pruna, you gain access to the most advanced optimization engine, capable of smashing any AI model with the latest compression methods for unmatched performance.
AI models are getting bigger, demanding more GPUs, slowing performance, and driving up costs and emissions. ML practitioners are left burdened with solving these inefficiencies.