franter666

stable-diffusion-webui

Stable Diffusion web UI

llama.cpp

LLM inference in C/C++

Prompt-Engineering-Guide

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

CVPR2024-Papers-with-Code

CVPR 2024 论文和开源项目合集

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

LLMSurvey

The official GitHub page for the survey paper "A Survey of Large Language Models".

LAVIS

LAVIS - A One-stop Library for Language-Vision Intelligence

RAG_Techniques

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.

DeepCTR

Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

causalml

Uplift modeling and causal inference with machine learning algorithms

The-Art-of-Linear-Algebra-zh-CN

Graphic notes on Gilbert Strang's "Linear Algebra for Everyone", 线性代数的艺术中文版, 欢迎PR.

llm-viz

3D Visualization of an GPT-style LLM

EconML

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 goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

Otter

🦦 Otter, a multi-modal model based on OpenFlamingo (open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT and showcasing improved instruction-following and in-context learning ability.

DeepCTR-Torch

【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

Diffusion-Models-Papers-Survey-Taxonomy

Diffusion model papers, survey, and taxonomy

End-to-end-Autonomous-Driving

[IEEE T-PAMI 2024] All you need for End-to-end Autonomous Driving

DeepMatch

A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.

DenoisingDiffusionProbabilityModel-ddpm-

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.

Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising

Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Ranking (CTR/CVR prediction), Post Ranking, Large Model (Generative Recommendation, LLM), Transfer learning, Reinforcement Learning and so on.

awesome-normalizing-flows

Awesome resources on normalizing flows.

FuxiCTR

A configurable, tunable, and reproducible library for CTR prediction https://fuxictr.github.io

causalTree

Working repository for Causal Tree and extensions

Point-Bind_Point-LLM

Align 3D Point Cloud with Multi-modalities for Large Language Models

dragonnet

Efficient_Foundation_Model_Survey

Survey Paper List - Efficient LLM and Foundation Models

SLidR

Official PyTorch implementation of "Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data"

MLInference

CTL

A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python

faiss-server

faiss serving :)