#python #document_understanding #language_generation #language_understanding #layoutlm #minilm #nlp #pre_trained_model #s2s_ft #small_pre_trained_model #unilm

https://github.com/microsoft/unilm

#typescript #document_object_model #dom #dom_api #dom_manipulation #html #javascript

https://github.com/phuoc-ng/html-dom

#javascript #api #document #documentation_tool #showdoc

https://github.com/star7th/showdoc

#python #computer_vision #deep_learning #detectron2 #document_image_analysis #document_image_processing #document_layout_analysis #layout_analysis #layout_parser #object_detection #ocr

https://github.com/Layout-Parser/layout-parser

#python #data_mining #data_science #document_similarity #fasttext #gensim #information_retrieval #machine_learning #natural_language_processing #neural_network #nlp #topic_modeling #word_embeddings #word_similarity #word2vec

https://github.com/RaRe-Technologies/gensim

#python #bert #document_embedding #pre_trained_language_models #semantic_search #sentence_encoder #sentence_transformers #text_search #text_semantic_similarity #top2vec #topic_modeling #topic_modelling #topic_search #topic_vector #word_embeddings

https://github.com/ddangelov/Top2Vec

#rust #backend_as_a_service #cloud_database #collaborative #database #database_as_a_service #developer_tools #devtools #distributed #distributed_database #document_database #graph_database #hacktoberfest #iot_database #nosql #realtime_database #serverless #sql #surreal #surrealdb #web

https://github.com/surrealdb/surrealdb

#html #data_pipelines #deep_learning #document_ai #document_image_analysis #document_image_processing #document_parser #document_parsing #docx #donut #information_retrieval #langchain #machine_learning #ml #natural_language_processing #nlp #ocr #pdf #pdf_to_json #pdf_to_text #preprocessing

https://github.com/Unstructured-IO/unstructured

#python #document_retrieval #embeddings #llms

https://github.com/chroma-core/chroma

#go #database #document #ferretdb #golang #mongo #mongo_db #mongodb #mongodb_database #postgres #postgresql

https://github.com/FerretDB/FerretDB

#python #document_ai #document_image_analysis #document_layout_analysis #document_parser #document_understanding #layoutlm #nlp #ocr #publaynet #pubtabnet #pytorch #table_detection #table_recognition #tensorflow

https://github.com/deepdoctection/deepdoctection

#cplusplus #artificial_intelligence #computer_vision #document #document_analysis #document_intelligence #document_recognition #document_understanding #documentai #end_to_end_ocr #multimodal #multimodal_deep_learning #ocr #scene_text_detection #scene_text_detection_recognition #scene_text_recognition #text_detection #text_recognition #vision_language #vision_language_model #vision_language_transformer

https://github.com/AlibabaResearch/AdvancedLiterateMachinery

#python #beit #beit_3 #bitnet #deepnet #document_ai #foundation_models #kosmos #kosmos_1 #layoutlm #layoutxlm #llm #minilm #mllm #multimodal #nlp #pre_trained_model #textdiffuser #trocr #unilm #xlm_e

Microsoft is developing advanced AI models through large-scale self-supervised pre-training across various tasks, languages, and modalities. These models, such as Foundation Transformers (Magneto) and Kosmos-2.5, are designed to be highly generalizable and capable of handling multiple tasks like language understanding, vision, speech, and multimodal interactions. The benefit to users includes state-of-the-art performance in document AI, speech recognition, machine translation, and more, making these models highly versatile and efficient for a wide range of applications. Additionally, tools like TorchScale and Aggressive Decoding enhance stability, efficiency, and speed in model training and deployment.

https://github.com/microsoft/unilm

#python #agent #agents #ai_search #chatbot #chatgpt #data_pipelines #deep_learning #document_parser #document_understanding #genai #graph #graphrag #llm #nlp #pdf_to_text #preprocessing #rag #retrieval_augmented_generation #table_structure_recognition #text2sql

RAGFlow is an open-source tool that helps businesses answer questions accurately using large language models and deep document understanding. It extracts information from various complex data formats, such as Word documents, Excel files, and web pages, and provides grounded citations to support its answers. You can try a demo online or set it up on your own server using Docker. The setup is relatively straightforward, requiring a few steps like cloning the repository, building the Docker image, and configuring the system settings. RAGFlow offers key features like template-based chunking, reduced hallucinations, and compatibility with multiple data sources, making it a powerful tool for truthful question-answering capabilities. This benefits users by providing reliable and explainable answers, streamlining their workflow, and supporting integration with their business systems.

https://github.com/infiniflow/ragflow

#python #ai4science #document_analysis #extract_data #layout_analysis #ocr #parser #pdf #pdf_converter #pdf_extractor_llm #pdf_extractor_pretrain #pdf_extractor_rag #pdf_parser #python

MinerU is a tool that converts PDFs into machine-readable formats like markdown or JSON. Here are the key benefits and features MinerU removes headers, footers, and other unnecessary elements to ensure the text is semantically coherent and in human-readable order, even for complex layouts.
- **Structure Preservation** It extracts images, image descriptions, tables, and table titles.
- **Formula Conversion** Recognizes tables and converts them to LaTeX or HTML format.
- **OCR Support** Supports multiple output formats and various visualization results.
- **GPU and CPU Compatibility**: Works on both CPU and GPU environments, compatible with Windows, Linux, and Mac.

You can try MinerU through an online demo, a quick CPU demo, or by using a GPU for faster processing. For detailed usage, refer to the command line options, API integration, and deployment guides provided.

https://github.com/opendatalab/MinerU

#ruby #daisyui #document_signing #documents #e_signature #github_catalyst #hotwired_turbo #legaltech #open_source #pdf #pdf_sign #pdf_signature #ruby_on_rails #self_hosted #tailwindcss #vuejs #webpack

DocuSeal is a free and open-source platform that helps you fill and sign documents online easily. You can create PDF forms with various field types like signatures, dates, and checkboxes, and these forms can be filled and signed on any device. It offers features like automated emails, multiple language support, and integration with cloud storage services. The platform is mobile-optimized and has tools for user management and API integrations. This makes it convenient for businesses to integrate document signing into their apps, reducing costs and ensuring security and compliance. You can try it out with a live demo or deploy it quickly using various hosting options.

https://github.com/docusealco/docuseal