A practical guide to running lightweight LLMs using python

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With the rise of multimodal large language models (LLMs), we can now interact with them in more ways than just typing text, such as using audio inputs. OpenAI recently released a voice feature for ChatGPT, allowing one to speak directly to the chat platform. This opens up a number of novel opportunities and applications built around it.

As machine learning and data science practitioners, this is an exciting time to be involved. Using OpenAI Real-time speech-to-speech APIsyou can create a voice assistant powered by these multimodal LLMs. However, if you are interested in open source libraries, you can also create a voice assistant, completely in a native environment and without subscribing to proprietary APIs!

1. Data privacy
2. No limit on API calls.
3. Fine tuning models

First, I believe most people who use mainstream generative AI chatbots are aware of the data that was transmitted through their servers. Many people may be concerned with the issue of data privacy…