Lo ra

Serving Voice AI at $1/hr: Open-source, LoRAs, Latency, Load Balancing - Neil Dwyer, Gabber

Serving Voice AI at $1/hr: Open-source, LoRAs, Latency, Load Balancing - Neil Dwyer, Gabber

An in-depth look at Gabber's experience deploying the Orpheus text-to-speech model to production, covering latency optimization, high-fidelity LoRa-based voice cloning, and a cost-effective inference stack using vLLM and a consistent hash ring for load balancing.

Make some noise: Teaching the language of audio to an LLM using sound tokens

Make some noise: Teaching the language of audio to an LLM using sound tokens

Shivam Mehta from KTH presents a method for teaching Large Language Models (LLMs) to understand and generate audio by treating it as a discrete language. The approach involves a two-step process: first, creating an ultra-low bitrate (0.293 kbps) audio representation using a causal variational autoencoder, and second, fine-tuning a Llama 7B model with these audio tokens using LoRA.