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[NeurIPS 2024 Best Paper][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An *ult…
This repository contains implementations and illustrative code to accompany DeepMind publications
The official GitHub page for the survey paper "A Survey on Mixture of Experts in Large Language Models".
A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour
Must-read Papers on Large Language Model (LLM) Planning.
PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722
Implements the paper "Wukong: Towards a Scaling Law for Large-Scale Recommendation" from Meta.
The official Meta Llama 3 GitHub site
Pytorch code for experiments on Linear Transformers
The boundary of neural network trainability is fractal
Code for CRATE (Coding RAte reduction TransformEr).
A Production-ready Reinforcement Learning AI Agent Library brought by the Applied Reinforcement Learning team at Meta.
Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implicit Bayesian Inference"
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
This project aim to reproduce Sora (Open AI T2V model), we wish the open source community contribute to this project.
A curated list of awesome anomaly detection resources
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
🦜🔗 Build context-aware reasoning applications
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs o…
We view Large Language Models as stochastic language layers in a network, where the learnable parameters are the natural language prompts at each layer. We stack two such layers, feeding the output…
Code and data for the paper "Bridging RL Theory and Practice with the Effective Horizon"
LLMs build upon Evol Insturct: WizardLM, WizardCoder, WizardMath