spotlight

Hey HN, when building ML systems for industrial AI, we have learned that data inspection is critical during the ML development process. We are also big fans of the Hugging Face ecosystem. That is why we built an integration to our data exploration tool Spotlight that allows you to interactively explore Hugging Face datasets with one line of code. Spotlight lets you leverage model results such as predictions and embeddings to gain a deeper understanding in data segments and model failure modes. Currently, many many NLP, CV, Audio and multimodal datasets are supported both locally and on the hub. You can find more info on the Hugging Face blog: https://huggingface.co/blog/scalable-data-inspection Link to repo: https://github.com/Renumics/spotlight Happy to hear your feedback!

Hey HN, We built a library to interactively explore unstructured datasets directly from a dataframe: https://github.com/Renumics/spotlight Some background: We have worked on different ML solutions over the years, mainly in the industrial AI space. A crucial step for us is always to inspect and explore the data interactively with the team and the customer. This is true throughout the dev process: During EDA, model debugging, model comparison and monitoring. We have tried many different options for visualizing unstructured datasets in the past: Notebooks, dash apps, custom react apps, HTML reports... However, these options were either very time-consuming to develop/maintain or not interactive enough or both. Our goal with Spotlight is to provide visualization for multimodal data with one line of code. Currently, Spotlight supports most unst