conorhassan

AutoGPT

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

transformers

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

stanford_alpaca

Code and documentation to train Stanford's Alpaca models, and generate the data.

chatbot-ui

AI chat for every model.

tinygrad

You like pytorch? You like micrograd? You love tinygrad! ❤️

evals

Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.

pytorch-deep-learning

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

flower

Flower: A Friendly Federated Learning Framework

releasing-research-code

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

conditional-flow-matching

TorchCFM: a Conditional Flow Matching library

bayesian-torch

A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch

GPJax

Gaussian processes in JAX.

pytensor

PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.

substra

Low-level Python library used to interact with a Substra network

synjax

FLamby

Cross-silo Federated Learning playground in Python. Discover 7 real-world federated datasets to test your new FL strategies and try to beat the leaderboard.

llamabot

Pythonic class-based interface to LLMs

MicroCanonicalHMC

MCHMC: sampler from an arbitrary differentiable distribution

simple-pytree

A dead simple Python package for creating custom JAX pytree objects

substra-backend

Backend of the Substra software

GFlowNet-EM

Code for GFlowNet-EM, a novel algorithm for fitting latent variable models with compositional latents and an intractable true posterior.

admm_lasso

Lasso with ADMM in Python/MPI

haikumodels

Pretrained models for Jax/Haiku; MobileNet, ResNet, VGG, Xception.

GVIPublic

Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)

generalized-diffusion

fed_cvae

Code for novel methods for one-shot Federated Learning under high statistical heterogeneity.

pi-vae

Code for utilising VAE as means of doing exact MCMC inference in complex high-dimensional space

ParEM

Code for "Particle algorithms for maximum likelihood training of latent variable models" (Kuntz, Lim, Johansen, AISTATS, 2023).

JaxKern

Kernel functions in JAX.

PriorCVAE