This put up is a technical put up summarizing my expertise with the Ray library for distributed information processing and showcasing an instance of utilizing Ray for scalable offline batch inference.
Not too long ago, I needed to put together a dataset for Imaginative and prescient LLM coaching. The standard of the coaching dataset is vital for the success of the coaching and we wanted to develop instruments for processing massive quantities of knowledge. The objective is to ensure the information feeding the mannequin is managed and prime quality.
Why a lot effort to create a dataset? Isn’t amount the key of LLM?
It’s not. First, Let me share why engineering effort must be given to establishing and filtering a superb dataset.
Within the present race for the event of basis fashions, many new fashions emerge each month on the high of the SOTA benchmarks. Some firms or laboratories share the weights with the open-source group. They often even share checkpoints and coaching scripts.
Nevertheless, the steps of creation and curation of the coaching datasets are hardly ever shared. For…