charleneleong-ai

kun

amplify-vue-website

Website resources for AWS Amplify and Vue website test

cleanlab

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

cocoapi

COCO API - Dataset @ http://cocodataset.org/

data2vec-pytorch

PyTorch implementation of "data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language" from Meta AI

dotfiles

EVA

Exploring the Limits of Masked Visual Representation Learning at Scale (https://arxiv.org/abs/2211.07636)

gridsome-starter-bootstrap

lightly

A python library for self-supervised learning on images.

mmsegmentation

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

notebooks

Set of Jupyter Notebooks linked to Roboflow Blogpost and used in our YouTube videos.

nvitop

An interactive NVIDIA-GPU process viewer and beyond, the one-stop solution for GPU process management.

OneFormer

[Preprint] OneFormer: One Transformer to Rule Universal Image Segmentation, 2022

python_for_microscopists

https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1

Smartphone-HID-App

thuml_tf_vae

vectorhub

Vector Hub - Library for easy discovery, and consumption of State-of-the-art models to turn data into vectors. (text2vec, image2vec, video2vec, graph2vec, bert, inception, etc)

big_T_ROS_navigation

Alpaca-Turbo

Web UI to run alpaca model locally

awesome-long-tail-learning

awesome-mixture-of-experts

A collection of AWESOME things about mixture-of-experts

generative-ai-for-beginners

12 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

giskard

🐢 The testing framework for ML models, from tabular to LLMs

llm-course

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

m2

Repo for "Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture"

MetisFL

MetisFL is a federated learning framework that allows developers to easily federate their machine learning workflows and train their models across distributed data silos without ever collecting the data in a centralized location. The core of the framework is written in C++ and focuses on scalability, speed and resiliency.

mrcnn-docker

multimodal

TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

shap-e

Generate 3D objects conditioned on text or images

torchscale

Foundation Architecture for (M)LLMs