Introduction GraphRAG (Graph Structure Based Retrieval Enhanced Generation) is an advanced retrieval and generation method. It combines the advantages of graph data structures with the capabilities of Large Language Models (LLMs) to overcome some of the limitations of traditional RAG systems. https://github.com/adithya-s-k/AI-Engi...
INTRODUCTION Intelligent body based approach to enhance retrieval augmented generation. Multi-Document Agentic RAG (Retrieval Augmented Generation) is an advanced information retrieval and generation method that combines multi-document processing, intelligent body systems, and large...
Notes: https://colab.research.google.com/github/run-llama/llama_index/blob/main/docs/docs/examples/multi_modal/gpt4v_multi_modal_ retrieval.ipynb
📚 Library Structure Model/Catalog Description and Content Axolotl Framework for fine-tuning language models Gemma Google's latest implementation of the Great Language Model - finetune-gemma.ipynb - gemma-sft.py - Gemma_finetuning_notebook. ipynb fine-tuning notebooks and scripts LLama2 M...
Welcome to the AI Agents section of the AI Engineering Academy! This module explores the fascinating world of AI agents, from basic patterns to practical applications. Learn how to create, orchestrate, and deploy intelligent agents that can perform complex tasks and reason about their environment. 📚 Repository Structure Category Components ...
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