A large language model (LLM) is a type of machine learning model designed for understanding, generating, and interacting with human language. These models are trained on extensive datasets containing text from books, articles, websites, and other sources to learn patterns, context, and semantics in language. LLMs are widely used in applications like chatbots, code generation, translation, summarization, and more. They are often built using transformer architectures and are central to the field of generative AI.
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本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
[ECCV 2024 Oral] DriveLM: Driving with Graph Visual Question Answering
Open source project for data preparation for GenAI applications
Streaming highlighting with Shiki. Useful for highlighting text streams like LLM outputs.
🔥🔥🔥 A curated list of papers on LLMs-based multimodal generation (image, video, 3D and audio).
The repository has collected a batch of noteworthy MLSys bloggers (Algorithms/Systems)
Hallucinations (Confabulations) Document-Based Benchmark for RAG. Includes human-verified questions and answers.
Samples using AI and Azure SQL DB
A comprehensive guide to LLM evaluation methods designed to assist in identifying the most suitable evaluation techniques for various use cases, promote the adoption of best practices in LLM assessment, and critically assess the effectiveness of these evaluation methods.
Turn a stream of token into a parsable JSON object as soon as possible. Enable Streaming UI for AI app based on LLM.