Generative models: exploration to deployment

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 – Website • , GitHub • , LinkedIn • , X • Daniel Whitenack – Website • , GitHub • , X Show Notes:

BigDLArticle: Making LLMs even more accessible with bitsandbytes, 4-bit quantization and QLoRAPrevious episode: Running large models on CPUsBaseten’s TrussSeldonHugging Face’s TGIIntel Gaudi 2Intel TDX Something missing or broken? PRs welcome!