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verl: Volcano Engine Reinforcement Learning for LLMs
微舆：人人可用的多Agent舆情分析助手，打破信息茧房，还原舆情原貌，预测未来走向，辅助决策！从0实现，不依赖任何框架。
高性能 高精度 大陆车牌、港澳车牌、台湾车牌 韩国车牌(South Korea LPR)识别 代码开源(ncnn移植）
🌟100+ 原创 LLM / RL 原理图📚，《大模型算法》作者巨献！💥（100+ LLM/RL Algorithm Maps ）
EasyR1: An Efficient, Scalable, Multi-Modality RL Training Framework based on veRL
Build resilient language agents as graphs.
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Official PyTorch Implementation of "Diffusion Transformers with Representation Autoencoders"
Detect Anything via Next Point Prediction (Based on Qwen2.5-VL-3B)
Ongoing research training transformer models at scale
An AI agent development platform with all-in-one visual tools, simplifying agent creation, debugging, and deployment like never before. Coze your way to AI Agent creation.
利用AI大模型，一键生成高清短视频 Generate short videos with one click using AI LLM.
A pipeline parallel training script for diffusion models.
One-for-All Multimodal Evaluation Toolkit Across Text, Image, Video, and Audio Tasks
🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
Fully Local Manus AI. No APIs, No $200 monthly bills. Enjoy an autonomous agent that thinks, browses the web, and code for the sole cost of electricity. 🔔 Official updates only via twitter @Martin9…
Fully Open Framework for Democratized Multimodal Training
PPOCRLabelv2 is a semi-automatic graphic annotation tool suitable for OCR field, with built-in PP-OCR model to automatically detect and re-recognize data.
Demonstration of running a native LLM on Android device.
使用TensorRT推理GroundingDINO，推理速度提升3倍以上！
Effortless data labeling with AI support from Segment Anything and other awesome models.
[ECCV2024] API code for T-Rex2: Towards Generic Object Detection via Text-Visual Prompt Synergy
A simple yet powerful agent framework that delivers with open-source models
This is the third party implementation of the paper Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.
[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
DINO-X: The World's Top-Performing Vision Model for Open-World Object Detection and Understanding