Generative models: exploration to deployment (Practical AI #240)

What is the model lifecycle like for experimenting with and then deploying generative AI models? Although there are some similarities, this lifecycle differs somewhat from previous data science practices in that models are typically not trained from scratch (or even fine-tuned). Chris and Daniel give a high level overview in this effort and discuss model optimization and serving.

What is the model lifecycle like for experimenting with and then deploying generative AI models? Although there are some similarities, this lifecycle differs somewhat from previous data science practices in that models are typically not trained from scratch (or even fine-tuned). Chris and Daniel give a high level overview in this effort and discuss model optimization and serving.

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Featuring:

Chris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, Website

Show Notes:

BigDL
Article: Making LLMs even more accessible with bitsandbytes, 4-bit quantization and QLoRA
Previous episode: Running large models on CPUs
Baseten’s Truss
Seldon
Hugging Face’s TGI
Intel Gaudi 2
Intel TDX

Something missing or broken? PRs welcome!