xianyuanliu

langchain

🦜🔗 Build context-aware reasoning applications

Prompt-Engineering-Guide

🐙 Guides, papers, lecture, notebooks and resources for prompt engineering

netron

Visualizer for neural network, deep learning and machine learning models

ultralytics

NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

generative-models

Generative Models by Stability AI

pytorch_geometric

Graph Neural Network Library for PyTorch

nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Awesome-Multimodal-Large-Language-Models

:sparkles::sparkles:Latest Advances on Multimodal Large Language Models

Awesome-Diffusion-Models

A collection of resources and papers on Diffusion Models

cleanlab

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

nougat

Implementation of Nougat Neural Optical Understanding for Academic Documents

BayesianOptimization

A Python implementation of global optimization with gaussian processes.

gemma_pytorch

The official PyTorch implementation of Google's Gemma models

awesome-LLMs-In-China

**大模型

captum

Model interpretability and understanding for PyTorch

nvitop

An interactive NVIDIA-GPU process viewer and beyond, the one-stop solution for GPU process management.

CTranslate2

Fast inference engine for Transformer models

exllama

A more memory-efficient rewrite of the HF transformers implementation of Llama for use with quantized weights.

ColabFold

Making Protein folding accessible to all!

pymatgen

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.

SMAC3

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

HpBandSter

a distributed Hyperband implementation on Steroids

emukit

A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.

AIRS

Artificial Intelligence Research for Science (AIRS)

syne-tune

Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.

matgl

Graph deep learning library for materials

fusilli

A Python package housing a collection of deep-learning multi-modal data fusion method pipelines! From data loading, to training, to evaluation - fusilli's got you covered 🌸

matbench

Matbench: Benchmarks for materials science property prediction

Computer-Vision-Reading-Group

ScalableML

Teaching materials for module COM6012 Scalable Machine Learning, University of Sheffield, 2024