labml-app 0.5.14

Experiment logger and visualizer

Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Currently we focus on the capabilities needed for inferencing (scoring).

Horovod is a powerful distributed training framework for Python that allows you to train deep learning models across multiple GPUs and servers quickly and efficiently. It falls under the category of distributed computing libraries. Built on top of TensorFlow, PyTorch, and other popular deep learning frameworks, Horovod simplifies the process of scaling up your model training by handling the complexities of distributed training under the hood.

Deep Lake is a Database for AI powered by a unique storage format optimized for deep-learning and Large Language Model (LLM) based applications. It simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage for all workloads, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more.

Distributed Deep learning with Apache Spark with Keras.

PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.

ktrain is a wrapper for TensorFlow Keras that makes deep learning and AI more accessible and easier to apply

A standard framework for using Deep Learning for tabular data

Petastorm is a library enabling the use of Parquet storage from Tensorflow, Pytorch, and other Python-based ML training frameworks.