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We're design the stack to be fairly flexible. It's Python/Pytorch under the hood, with the ability to plug and play various off the shelf models. For ASR we sup
by TheEzEzz 3y ago
We're design the stack to be fairly flexible. It's Python/Pytorch under the hood, with the ability to plug and play various off the shelf models. For ASR we support GCP/AssemblyAI/etc, as well as a customized self-hosted version of Whisper that is tailored for stream processing. For the LLM we support fine-tuned GPT3 models, fine-tuned Google text-bison models, or locally hosted fine-tuned Llama models (and a lot of the project goes into how to do the fine-tuning to ensure accuracy and low latency). For the TTS we support Elevenlabs/GCP/etc, and they all tie into the latency reducing approaches.