A project to improve skills of large language models

A simple, performant and scalable Jax LLM!

A tool to configure, launch and manage your machine learning experiments.

Library for reading and processing ML training data.

🚀 High-performance file format for ML data storage with parallel I/O, random access, and efficient compression. Python bindings + Apache Beam integration for scalable data processing.

verl: Volcano Engine Reinforcement Learning for LLMs

xpk (Accelerated Processing Kit, pronounced x-p-k,) is a software tool to help Cloud developers to orchestrate training jobs on accelerators such as TPUs and GPUs on GKE.

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

A high-throughput and memory-efficient inference and serving engine for LLMs

SGLang is a fast serving framework for large language models and vision language models.

A JAX-native LLM Post-Training Library

Minimal, lightweight JAX implementations of popular models.

A Jekyll version of the Clean Blog theme by Start Bootstrap

TradingAgents: Multi-Agents LLM Financial Trading Framework

Ongoing research training transformer models at scale

Code for 'LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders'

MTEB: Massive Text Embedding Benchmark

A framework for few-shot evaluation of autoregressive language models.

Kss: A Toolkit for Korean sentence segmentation

CensorShipAPI to detect swear words or rude phrases

Plug and play modules to optimize the performances of your AI systems 🚀

Implementation of Muse: Text-to-Image Generation via Masked Generative Transformers, in Pytorch

🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

The official implementation of Autoregressive Image Generation using Residual Quantization (CVPR '22)