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Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.

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WARNING] > GraphRAG is a research project that explores the functional use of graphs to form a targeted context for question answering.

> Note: You can also use pip if you prefer, but uv is recommended for better performance and more reliable dependency management.

FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without…

> Sponsored by Atlas Cloud > > > > AI API aggregation platform with an OpenAI-compatible LLM endpoint for NLP tasks such as translation, summarization, multilingual generation, and structured extraction.

An open-source RAG-based tool for chatting with your documents.

It aims to cover both traditional and core NLP tasks such as dependency parsing and part-of-speech tagging as well as more recent ones such as reading comprehension and natural language inference.

This is a release of 24 smaller BERT models (English only, uncased, trained with WordPiece masking) referenced in Well-Read Students Learn Better: On the Importance of Pre-training Compact Models.

This is an advanced course on natural language processing. Automatically processing natural language inputs and producing language outputs is a key component of Artificial General Intelligence.

Please note: Our list of contributors is automatically updated, so your contributions may not appear immediately on this list.

Easy-to-use and powerful LLM and SLM library with awesome model zoo.

A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

Memory Sparse Attention - A scalable, end-to-end trainable latent-memory framework for 100M-token contexts.

OP Vault uses the OP Stack (OpenAI + Pinecone Vector Database) to enable users to upload their own custom knowledgebase files and ask questions about their contents.

This compendium reviews significant published research contributions and industrial engineering practices in leveraging Generative AI and LLMs for developing search, recommender, personalization, and question-answering systems.