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Our Process for Llama2 Finetuning

Python framework for artificial text detection: NLP approaches to compare natural text against generated by neural networks.

Empower Truly Autonomous AI Agents through our Experimental Adversarial and Evolutionary Reinforcement Learning Framework. Join our Community: https://t.me/evolveRL_portal

Official PyTorch Implementation for the "Learning on Model Weights using Tree Experts" paper (CVPR 2025).

A vector database for querying meaningfully similar data.

End-to-end deployment of Azure OpenAI applications using Redis Enterprise as a vector database.

KoutenDB: locality-aware NoSQL document/vector database built around rings and orbit-inspired retrieval

Nautobot Model Context Protocol (MCP) Server - Contains STDIO and HTTP Deployments with Embedding Search and RAG.

A rag application to chat with your documents with the help of gemini, pinecone and Next.js

Production-ready Retrieval Augmented Generation (RAG) system with hybrid retrieval, advanced evaluation metrics, and monitoring. Build enterprise LLM applications with reduced hallucinations, better context management, and comprehensive observability.

For your repository, issuedigger will notify authors of new issues about similar, previously submitted ones, saving manual digging. Implemented as a single, AI-enabled Cloudflare Worker.

Learn TypeScript chatting effortlessly with AI

Miscellaneous codes and writings for MLOps

Add different kinds of data: Youtube videos, PDFs, Internet links and ask questions based on the content provided using an intuitive UI.

Decentralized memory-sharing protocol for AI agent

The Facial Recognition Based Attendance System is an automated solution designed to streamline attendance management in educational institutions. By utilizing advanced facial recognition technology, the system eliminates manual attendance processes, reduces proxy attendance, and provides real-time attendance tracking with comprehensive reporting .

Explore cutting-edge Redis capabilities for Vector Similarity Search, Hybrid Search (Vector Similarity + Meta Search), Semantic Caching, and an advanced RAG model integrated with a Language Model (LLM) Chatbot. Unlock the full potential of Redis as a vector database with this comprehensive showcase of powerful features.

A Multi-Agent RAG platform using Vector DBs and AI models to accurately answer AML/CFT compliance queries.

Embeddable vector database for Rust and Python. HNSW indexing, metadata filtering, hybrid search, and snapshots. The SQLite of vector search.

This project implements RAG using OpenAI's embedding models and LangChain's Python library