llmsresearch/llm-flashcards
211 free visual cards about large language models, from tokenization to deployment. Full collection: 376 cards.
A complete collection of RAG interview questions, answers (1619 questions & 52 RAG types), system design scenarios, architecture patterns, and production-ready concepts.
$ git clone https://github.com/ather-techie/rag-interview-system.git211 free visual cards about large language models, from tokenization to deployment. Full collection: 376 cards.
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This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.
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Learn AI and LLMs from scratch using free resources
Powerful web application that combines Streamlit, LangChain, and Pinecone to simplify document analysis. Powered by OpenAI's GPT-3, RAG enables dynamic, interactive document conversations, making it ideal for efficient document retrieval and summarization.
Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs ,META LLAMA3 , Agents.
Data from GitHub · snapshot Nov 13, 2026