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Label Studio is an open source data labeling and annotation platform for multi-modal data, including text, images, audio and time series. It lists uses such as LLM and agent evaluation, computer vision, NLP and document tasks, and audio transcription. It offers API, Python SDK and webhooks, and is available via pip, Homebrew, Git and Docker.
A guide to MLOps is an open-source tutorial from the Swiss AI Center team that walks engineers and small teams from notebook experiments to production. It covers local training and model evaluation, moving the model to the cloud, serving and deploying, monitoring and maintaining, and labeling data and retraining, using tools such as DVC, Git, GitHub Actions, CML, Docker, BentoML, Fluent Bit, Evidently AI, and Label Studio.
