Latex-format paper templates, including Elsevier, arXiv and IEEE Access.

Implementation of Griffin from the paper: "Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models"

Automatically evaluate your LLMs in Google Colab

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

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

LLM101n: Let's build a Storyteller

An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.

LLM Transparency Tool (LLM-TT), an open-source interactive toolkit for analyzing internal workings of Transformer-based language models. *Check out demo at* https://huggingface.co/spaces/facebook/l…

Foundation Architecture for (M)LLMs

Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.

⚡ Build your chatbot within minutes on your favorite device; offer SOTA compression techniques for LLMs; run LLMs efficiently on Intel Platforms⚡

Kolmogorov Arnold Networks

Nonlinear Progamming with CasADi

Reinforcement Learning with Model Predictive Control

PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL

Adaptive control-oriented meta-learning for nonlinear systems

Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gym environments

Code for "Learning Control-Oriented Dynamical Structure from Data" by Spencer M. Richards, Jean-Jacques Slotine, Navid Azizan, and Marco Pavone.

Stable_Estimator_of_Dynamical_System_Algorithm

(Work in progress) Python implementation of Stable Estimator of Dynamical Systems (SEDS).

Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling

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

Gaussian Mixture Regression

Code for "Learning Control-Oriented Dynamical Structure from Data" by Spencer M. Richards, Jean-Jacques Slotine, Navid Azizan, and Marco Pavone.

Official PyTorch implementation for a conditional diffusion probability model in BEV perception

This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.

The Noise Contrastive Estimation for softmax output written in Pytorch

Official pytorch implementation for the paper "Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification"

[NeurIPS 2023] Neural Lyapunov Control for Discrete-Time Systems