Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
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Updated
Sep 21, 2026 - Python
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
可私有部署的多租户知识智能体平台:统一 RAG、知识图谱、多智能体、MCP/Skills、沙盒与权限管理。Yuxi = Cloud Agents + Knowledge RAG, Self-hosted knowledge agent platform for RAG, knowledge graphs and multi-agent workflows.
LLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows
Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022
Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.
A Repo For Document AI
开箱即用的AI标书编写工具,标书AI生成工具,投标工具箱、知识库、标书查重、废标项检查,完全开源免费,欢迎使用
在保留版面、公式与结构的前提下进行 PDF 翻译,适用于科研与技术文档
Extract structured data and insights from documents using LLMs and decision models
A curated list of resources for Document Understanding (DU) topic
Get clean data from tricky documents, powered by vision-language models ⚡
TurboOCR, >200 img/s OmnidocBench. TensorRT FP16, PP-OCRv6, HTTP + gRPC
PDF to markdown using vision LLMs — tables, layouts, and structure preserved
Turn documents into AI-ready Markdown with visual understanding
Agentic RAG for local and self-hosted document search: hybrid retrieval, reranking and multimodal RAG on embedded LanceDB, with Docling parsing and an MCP server
ParseBench - A Document Parsing Benchmark for AI Agents
Official PyTorch implementation of LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding (ACL 2022)
AI-enabled Intelligent Document Processing for Python: 12+ LLM backends, Pydantic schemas, self-hosted OCR (Nanonets-OCR2-3B), auto-schema discovery, HITL review, prod FastAPI server. AGPL-3.0 + commercial.
Visual document analysis studio powered by Docling — configure the extraction pipeline, inspect text, tables and bounding boxes in the browser, then chunk, embed and index into OpenSearch and Neo4j.
Algorithms, papers, datasets, performance comparisons for Document AI.
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