Illustrated with an instance of Multimodal offline batch inference with CLIP
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.
Just lately, I needed to put together a dataset for Imaginative and prescient LLM coaching. The standard of the coaching dataset is essential for the success of the coaching and we wanted to develop instruments for processing giant quantities of knowledge. The objective is to verify the information feeding the mannequin is managed and top 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 needs to 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 corporations or laboratories share the weights with the open-source neighborhood. They generally even share checkpoints and coaching scripts.
Nonetheless, the steps of creation and curation of the coaching datasets are hardly ever shared. For…