Popular GitHub Repositories for Configuration Baseline

FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without the need for extensive setup or configuration.

A delightful Ruby way to work with AI. No configuration madness, no complex callbacks, no handler hell – just beautiful, expressive Ruby code.

收录NLP竞赛策略实现、各任务baseline、相关竞赛经验贴（当前赛事、往期赛事、训练赛）、NLP会议时间、常用自媒体、GPU推荐等，持续更新中

A conversational Q&A agent configuration system, self-hosted deployment solutions, and a convenient all-in-one application SDK, allowing you to create intelligent Q&A bots for your GitHub repositories

AutoGroq is a groundbreaking tool that revolutionizes the way users interact with Autogen? and other AI assistants. By dynamically generating tailored teams of AI agents based on your project requirements, AutoGroq eliminates the need for manual configuration and allows you to tackle any question, problem, or project with ease and efficiency.

A simple baseline for 3d human pose estimation in tensorflow. Presented at ICCV 17.

An open source DevOps tool for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI artifact.

This repository allows you to get started with a gui based training a State-of-the-art Deep Learning model with little to no configuration needed! NoCode training with TensorFlow has never been so easy.

Fast-BEV: A Fast and Strong Bird’s-Eye View Perception Baseline

ROS-LLM is a framework designed for embodied intelligence applications in ROS. It allows natural language interactions and leverages Large Language Models (LLMs) for decision-making and robot control. With an easy configuration process, this framework allows for swift integration, enabling your robot to operate with it in as little as ten minutes.

The repository is for safe reinforcement learning baselines.

This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. NoCode training with YOLOv4 and YOLOV3 has never been so easy.

Achieve the llama3 inference step-by-step, grasp the core concepts, master the process derivation, implement the code.

A powerful baseline for image classification, face recognition and image retrieval with Pytorch

Shared starter template configuration and CLAUDE.md memory bank system for Claude Code

Code implementation of "Learning Efficient Online 3D Bin Packing on Packing Configuration Trees". We propose to enhance the practical applicability of online 3D Bin Packing Problem (BPP) via learning on a hierarchical packing configuration tree which makes the deep reinforcement learning (DRL) model easy to deal with practical constraints and well-performing even with continuous solution space.

Official implementation of Paper Future Frame Prediction for Anomaly Detection -- A New Baseline, CVPR 2018

Keyphrase or Keyword Extraction 基于预训练模型的中文关键词抽取方法（论文SIFRank: A New Baseline for Unsupervised Keyphrase Extraction Based on Pre-trained Language Model 的中文版代码）

A simple baseline for 3d human pose estimation in PyTorch.

Enterprise self-hosted Bitcoin Core automated trading software and trading bot, with DCA bot configuration, on-premise TWAP/VWAP strategy scripts, dynamic fee management, CCXT exchange adapter, compliance reporting, OTC desk integration, HSM hardware signing, real-time PnL metrics, and advanced strategy view windows.