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Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.
Lightning-fast serving engine for AI models. Flexible. Easy. Enterprise-scale.
"EasyRec: Simple yet Effective Language Model for Recommendation"
mlpack: a fast, header-only C++ machine learning library
Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
DuckDB is an analytical in-process SQL database management system
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
Modin: Scale your Pandas workflows by changing a single line of code
real time face swap and one-click video deepfake with only a single image
mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
Official inference repo for FLUX.1 models
libSQL is a fork of SQLite that is both Open Source, and Open Contributions.
Meta Learning for Semi-Supervised Few-Shot Classification
Reverb is an efficient and easy-to-use data storage and transport system designed for machine learning research
An opinionated list of awesome Python frameworks, libraries, software and resources.
🆔 A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.
Python toolkit for quantitative finance
Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, Phi, MiniCPM, etc.) on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc,…
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Enjoy the magic of Diffusion models!
Finetune Llama 3.1, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory