Entry
Appears in 8 awesome lists
Standard data-centric AI package for data quality and machine learning, automatically detecting label errors, outliers, and dataset issues to improve scientific dataset reliability and model performance (11K+ stars, MIT License)
Section: Weak Supervision & Auto-Labeling · Standard data-centric AI package for data quality and machine learning, automatically detecting label errors, outliers, and dataset issues to improve scientific dataset reliability and model performance (11K+ stars, MIT License)
Section: Miscellaneous Tools · Python library for data-centric AI and automatically detecting various issues in ML datasets
Section: Python · The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Section: Data Validation · Python library for data-centric AI and machine learning with messy, real-world data and labels.
Section: Data Annotation and Synthesis · Python library for data-centric AI. Can automatically: find mislabeled data, detect outliers, estimate consensus + annotator-quality for multi-annotator datasets, suggest which data is best to (re)label next.
Section: Data Science and Analytics · Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Section: Data-centric AI · The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Section: General · Machine learning with noisy labels, finding mislabelled data, and uncertainty quantification. Also see awesome list below. doubtlab - Find bad or noisy labels.
How to use the Hexagon Delegate to speed up model inference on mobile and edge devices. Also see blog post Accelerating TensorFlow Lite on Qualcomm Hexagon DSPs.
(label: good first issue) PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.
Comet's open-source AI observability and evaluation platform: deep tracing of LLM calls, conversation logging, and agent activity, plus built-in eval metrics, prompt versioning, guardrails, and the Opik Agent Optimizer. Worth including because it unifies observability, verification, and…
(formerly known as pytorch-transformers and pytorch-pretrained-bert) provides state-of-the-art general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet, CTRL...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in…
(from Hpcaitech) - A Unified Deep Learning System for Large-Scale Parallel Training (1D, 2D, 2.5D, 3D and sequence parallelism, and ZeRO protocol).
"Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it…
A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library. ray.io
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search,…