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OCR model that handles complex tables, forms, handwriting with full layout.
RTX 6000 Pro Wiki — Running Large LLMs (Qwen3.5-397B, Kimi-K2.5, GLM-5) on PCIe GPUs without NVLink
A polyglot document intelligence framework with a Rust core. Extract text, metadata, images, and structured data from 101 formats (115 file extensions) plus code intelligence for 371 code languages…
Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞
An MCP server that provides real-time information using Google Gemini's grounding capabilities
AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs
A lightweight sandboxing tool for enforcing filesystem and network restrictions on arbitrary processes at the OS level, without requiring a container.
A proxy for minimax-m2, enabling interleaved thinking, and tool calls.
WeDLM: The fastest diffusion language model with standard causal attention and native KV cache compatibility, delivering real speedups over vLLM-optimized baselines.
Alpaca dataset from Stanford, cleaned and curated
Build, deploy, and orchestrate AI agents. Sim is the central intelligence layer for your AI workforce.
SGLang is a high-performance serving framework for large language models and multimodal models.
A high-throughput and memory-efficient inference and serving engine for LLMs
[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.
Implements harmful/harmless refusal removal using pure HF Transformers
OpenDeepWiki is the open-source version of the DeepWiki project, aiming to provide a powerful knowledge management and collaboration platform. The project is mainly developed using C# and TypeScrip…
Open Source DeepWiki: AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories. Join the discord: https://discord.gg/gMwThUMeme
[ACL 2026] Open-source framework for holistic, structured repository-level documentation across multilingual codebases
Interactive, editable docs designed for coding agents
LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of function calling, memory, and ReAct patterns.
Benchmarking tool for vLLM inference performance with GPU monitoring