yufeihe1

grok-1

Grok open release

DeepSpeed

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

vllm

A high-throughput and memory-efficient inference and serving engine for LLMs

llama3

The official Meta Llama 3 GitHub site

llm.c

LLM training in simple, raw C/CUDA

dspy

DSPy: The framework for programming—not prompting—foundation models

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

ChatGLM3

ChatGLM3 series: Open Bilingual Chat LLMs | 开源双语对话语言模型

triton

Development repository for the Triton language and compiler

FlagEmbedding

Retrieval and Retrieval-augmented LLMs

GLM-4

GLM-4 series: Open Multilingual Multimodal Chat LMs | 开源多语言多模态对话模型

build-nanogpt

Video+code lecture on building nanoGPT from scratch

chatgpt-prompts-for-academic-writing

This list of writing prompts covers a range of topics and tasks, including brainstorming research ideas, improving language and style, conducting literature reviews, and developing research plans.

OpenRLHF

An Easy-to-use, Scalable and High-performance RLHF Framework (70B+ PPO Full Tuning & Iterative DPO & LoRA & Mixtral)

AgentTuning

AgentTuning: Enabling Generalized Agent Abilities for LLMs

pyreft

ReFT: Representation Finetuning for Language Models

Awesome-Language-Model-on-Graphs

A curated list of papers and resources based on "Large Language Models on Graphs: A Comprehensive Survey"

flash-attention-minimal

Flash Attention in ~100 lines of CUDA (forward pass only)

pytorch-frame

Tabular Deep Learning Library for PyTorch

MathGLM

Official Pytorch Implementation for MathGLM

llamafia.github

G-Retriever

Repository for G-Retriever

awesome-large-graph-model

Papers about large graph models.

Graph-LLM

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs

relbench

RelBench: Relational Deep Learning Benchmark

OneForAll

A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.

Awesome-Pretraining-for-Graph-Neural-Networks

A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).

GSLB

A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)

TAG-Benchmark

Benchmark

DECOR

Data and code for "DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection" (KDD 2023)