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

Examples and guides for using the OpenAI API

Google Research

The fastai deep learning library

A guidance language for controlling large language models.

This repository contains implementations and illustrative code to accompany DeepMind publications

Jupyter Interactive Notebook

Solve puzzles. Learn CUDA.

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K…

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…

Probabilistic reasoning and statistical analysis in TensorFlow

Solve puzzles. Improve your pytorch.

Homepage for STAT 157 at UC Berkeley

Bayesian optimization in PyTorch

Model API for GALACTICA

Fast and Easy Infinite Neural Networks in Python

Puzzles for learning Triton

Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, B…

Low-Cost Open Source Ventilator or PAPR

A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods

Superlinked is a Python framework for AI Engineers building high-performance search & recommendation applications that combine structured and unstructured data.

Introduction to Mathematical Computing with Python and Jupyter

Code associated with the paper **Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding**

Collection of the latest, greatest, deep learning optimizers (for Pytorch) - CNN, NLP suitable

A Python library for integrating model-based and judgmental forecasting

Improving generalization by controlling label-noise information in neural network weights.

An infrastructure for empirical research: Studying the limits of neural networks for computer vision tasks.