Steve WoodIn my previous post, Experiences in Fine-Tuning LLMs: Time + Power = Potato?, I covered my experiences around trying to fine-tune an LLM (large language model) with a dataset, which gave me less than stellar results. Ultimately, fine-tuning is best for a use-case where additional reasoning & logic needs to be added to an LLM, … Read More
Embarking on the journey to fine-tune large language models (LLMs) can often feel like setting sail into uncharted waters, armed with hope and a map of best practices. Yet, despite meticulous planning and execution, the quest for improved performance doesn’t always lead to the treasure trove of success one might anticipate. And I know you … Read More
Chariot Day is a tradition here at Chariot Solutions where our colleagues share what they’ve been thinking about and hacking on.
An overview of Spring Cloud Sleuth; a simple way to get the power of distributed tracing in your Spring Boot applications. Covers implementation, examples, and common pitfalls.
