nickb-

llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

litgpt

20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

pycon2024

Tutorial Materials for "The Fundamentals of Modern Deep Learning with PyTorch" workshop at PyCon 2024

transformers

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

sentinel2_superresolution

Super-resolution of 10 Sentinel-2 bands to 5-meter resolution, starting from L1C or L2A (Theia format) products.

NextViT-tf

A Tensorflow implementation of "Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios"

Next-ViT

machine-learning-book

Code Repository for Machine Learning with PyTorch and Scikit-Learn

MachineLearning-QandAI-book

Machine Learning Q and AI book

LLMs-from-scratch

Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step

HighResCanopyHeight

This repository provides inference code to compute canopy height maps from aerial images, as described in the paper "Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on Aerial Lidar".

t-simcne

Unsupervised visualization of image datasets using contrastive learning

ml-engineering

Machine Learning Engineering Open Book

nfnets-Tensorflow-2

Pre-trained NFNets with 99% of the accuracy of the official paper "High-Performance Large-Scale Image Recognition Without Normalization".

layer_masking

Code to reproduce our ICCV paper "Towards Improved Input Masking for Convolutional Neural Networks"

simpool

This repo contains the official implementation of ICCV 2023 paper "Keep It SimPool: Who Said Supervised Transformers Suffer from Attention Deficit?"

CLIP

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

global-canopy-height-model

This repository contains the code used in the paper: A high-resolution canopy height model of the Earth. Here, we developed a model to estimate canopy top height anywhere on Earth. The model estimates canopy top height for every Sentinel-2 image pixel and was trained using sparse GEDI LIDAR data as a reference.

EMP-SSL

This repository contains the implementation for the paper "EMP-SSL: Towards Self-Supervised Learning in One Training Epoch."

vicreg

VICReg official code base