RAPIDS Sample Notebooks

Material for gpu-mode lectures

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

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

Finetune Llama 3.1, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory

Efficient Triton Kernels for LLM Training

SkyPilot: Run AI and batch jobs on any infra (Kubernetes or 12+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface.

Llama 2 Everywhere (L2E)

LLM inference in C/C++

The official PyTorch implementation of Google's Gemma models

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

Train transformer language models with reinforcement learning.

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

Convert HTML to Markdown

Statsmodels: statistical modeling and econometrics in Python

BLAS-like Library Instantiation Software Framework

cuML - RAPIDS Machine Learning Library

GPU Accelerated t-SNE for CUDA with Python bindings

NumPy-like API accelerated with CUDA

Fast, flexible and easy to use probabilistic modelling in Python.

Sphinx theme for readthedocs.org