TokenSpeed is a speed-of-light LLM inference engine designed for agentic workloads, with TensorRT-LLM-level performance and vLLM-level usability. The goal is to be the most performant inference engine for production agentic workloads.
PaddleOCR converts PDF documents and images into structured, LLM-ready data (JSON/Markdown) with industry-leading accuracy.
Modern documents increasingly contain diverse multimodal content—text, images, tables, equations, charts, and multimedia—that traditional text-focused RAG systems cannot effectively process.
Evolving Multimodal Inference Programs: LLM-guided evolutionary search for accurate and efficient vision-language inference.
md and local files. yaml only adds optional UI metadata (display name, description, default prompt) for the ChatGPT/Codex skills UI, per OpenAI's skill spec — it does not limit the skill to OpenAI agents.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
SGLang is a high-performance serving framework for large language models and multimodal models.
LLM inference server with continuous batching & SSD caching for Apple Silicon — managed from the macOS menu bar
The Open-Source Multimodal AI Agent Stack: Connecting Cutting-Edge AI Models and Agent Infra
[Lumina具身智能社区] 具身智能技术指南 Embodied-AI-Guide
Gaussian blur reveals how Valen-Preview-0923 adapts its decisions and confidence as visual detail decreases. 2% at the strongest blur.
X-AnyLabeling: A lightweight, efficient, and unified cross-platform desktop application for annotating text, image, video, and multimodal data, combining versatile built-in tools with state-of-the-art AI models and flexible multi-format export.
Knowhere is a document parsing and retrieval system that turns complex, dirty files into persistent, navigable memory for AI agents—especially across local and offline document collections.
verl/HybridFlow: A Flexible and Efficient RL Post-Training Framework
The end of web parsing. The beginning of scalable pixel-native search. link:
This is an open collection of methodologies, tools and step by step instructions to help with successful training and fine-tuning of large language models and multi-modal models and their inference.
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TypeLLM brings type-safe generation to existing autoregressive LLMs without changing their architecture or weights. Inspired by TypeSafe AI's Jev, it lets models retain their native thinking and free-form generation while producing schema-guaranteed outputs through JSON Schema.
verl/HybridFlow: A Flexible and Efficient RL Post-Training Framework
Our managed platform runs both Surya, and variants of our highest accuracy model, Chandra.
Eight SDKs, one C++ core. A capability registry routes every call to the best engine on the device, and the Console manages your fleet from above.
An all-in-one VLA engineering platform for embodied AI — from data to real-robot deployment.
LightNav-0 is a compact generalist embodied navigation model that elicits the spatial intelligence of a pretrained vision-language model (Qwen3-VL) and aligns it with navigation, without task-specific prediction heads.
[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4o. 接近GPT-4o表现的开源多模态对话模型
5, our scalable data pipeline of environments, solvers, and verifiers. 5 Computer Use on Online-Mind2Web.
0-9B is a multimodal foundation model for general visual understanding, spatial reasoning, agentic tool use, and embodied-AI research. 5-9B language backbone with a C-RADIOv4-H vision encoder, supports text, images and videos with any-resolution visual input.
Our managed platform runs improved extraction with higher accuracy than the open weights, plus per-field verification, citations, and confidence scores.
5 vision-language model and integrates 3D perception, visual question answering, and motion planning within a unified framework. 5-4B serves as the shared VLM, with two external modules attached:
RoboICL is an in-context robot-control framework that adapts a frozen general-purpose vision-language model from demonstrations and its own execution history. It requires no robot-specific parameter update and no learned vision-language-action model.
28 2023] We now provide a llama 2 version of MiniGPT-4