This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.
Updated 2025-04-01 23:32:26 +03:00
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
Updated 2025-01-28 01:46:33 +03:00
Neo4j graph construction from unstructured data using LLMs
knowledge-graph
rag
graph
graph-rag
graph-search
graphdb
graphrag
langchain
neo4j
unstructured-data
vectordb
data-import
genai
Updated 2024-08-30 16:31:54 +03:00
LLM Analytics
Updated 2024-06-10 01:01:34 +03:00
Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks
llm
large-language-models
knowledge-graph
gpt
llama
prompt-engineering
llama2
rag
knowledge-base
sentence-transformers
gpt4
bert-models
bioinformatics
bioinformatics-algorithms
biomedical-applications
biomedical-informatics
context-aware
gpt35turbo
prompt-tuning
retrieval-augmented-generation
Updated 2024-06-08 14:12:55 +03:00
DNA foundation modeling from molecular to genome scale
Updated 2024-05-28 01:55:55 +03:00
Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineering
Updated 2024-03-14 00:13:46 +03:00
Training LLMs with QLoRA + FSDP
Updated 2024-03-08 17:58:09 +03:00
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Updated 2024-01-14 16:32:03 +03:00
Jupyter Notebooks to help you get hands-on with Pinecone vector databases
Updated 2023-10-11 20:04:55 +03:00
DSPy: The framework for programming with foundation models
Updated 2023-09-08 00:12:24 +03:00