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

A simple, performant and scalable Jax LLM!

Tensors and Dynamic neural networks in Python with strong GPU acceleration

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

Public facing notes page

A simplified and automated orchestration workflow to perform ML end-to-end (E2E) model tests and benchmarking on Cloud VMs across different frameworks.

🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Testing framework for Deep Learning models (Tensorflow and PyTorch) on Google Cloud hardware accelerators (TPU and GPU)

Hackable implementation of state-of-the-art open-source LLMs based on nanoGPT. Supports flash attention, 4-bit and 8-bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-l…

Sample applications for Google Kubernetes Engine (GKE)

TorchBench is a collection of open source benchmarks used to evaluate PyTorch performance.

Datasets, Transforms and Models specific to Computer Vision

This repository contains example code to build models on TPUs

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

fork from Nick's maskrcnn repo (https://docs.google.com/document/d/1pd3XOvCeMugiZ6y3adLZo3pAgqiWHitkASuUawEbECY/edit#)

Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy. Avoid writing scripts or custom code to deploy and update your applications — automat…

Ansible on Azure Lab playbooks and documentation

Open source documentation of Microsoft Azure

Assignment 4 of the Front End Javascript Frameworks AngularJS Overview Course in Coursera.com

This repo is for demonstration purposes only. Comments and issues may or may not be responded to.