a fast, scalable, multi-language and extensible build system

🚀 Accelerate inference and training of 🤗 Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Empowering everyone to build reliable and efficient software.

The Scala 3 compiler, also known as Dotty.

Apache Spark - A unified analytics engine for large-scale data processing

PyTorch native post-training library

An implementation of the Build Server Protocol for Bazel

Visual Studio Code

Pytorch to Keras/Tensorflow/TFLite conversion made intuitive

Bazel support for Visual Studio Code

Making large AI models cheaper, faster and more accessible

Bazel BSP Server

Property-based testing for Scala

Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed causal structure.

Framework and Language for Neurosymbolic Programming.

Beautiful Text-based User Interfaces for Scala

Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.

A type-safe TypeScript SQL query builder

Guide to using pre-trained large language models of source code

Hackable and optimized Transformers building blocks, supporting a composable construction.

Extremely fast Query Engine for DataFrames, written in Rust

Official Rust implementation of Apache Arrow

GPU accelerated deep learning and numeric computing for Scala 3.

Scala bindings for LibTorch

NOT MAINTAINED - A simple Rust like Result type for Python 3. Fully type annotated.

Set up your GitHub Actions workflow with a specific GraalVM distribution.

A curated list of papers, theses, datasets, and tools related to the application of Machine Learning for Software Engineering