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Enterprises Using MLOps, the Changing LLM Landscape, MLOps Pipelines // Chris Van Pelt // #192

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Discussion on LMS function call output, fine-tuning with QLORA, and LORA as an alternative for model configuration

This chapter explores the importance of exact function call output for processing outcomes with an LMS, as well as the success rate achieved through fine-tuning with QLORA. It also discusses how LORA serves as a default alternative for fine-tuning models, offering a good performance trade-off and easy configuration. The chapter highlights how QLORA utilizes a faster forward pass using a quantized version of the model for smaller GPUs.

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