Kyaw's repositories
langchain-tutorials
Overview and tutorial of the LangChain Library
GenerativeAIExamples
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
skills-code-with-codespaces
My clone repository
skills-copilot-codespaces-vscode
My clone repository
llamafile
Distribute and run LLMs with a single file.
copilot-prompts
Examples of prompts for Microsoft Copilot
Function-Calling-and-Data-Extraction-with-LLMs
Master the techniques of function-calling and structured data extraction with LLMs. Learn to enhance LLM capabilities, integrate web services, and build practical applications for real-world data usability.
redeval
Red-teaming LLM applications.
Mastering-GitHub-Copilot-for-Paired-Programming
An 8 Lesson course teaching everything you need to know about harnessing GitHub Copilot and an AI Paired Programing resource.
AI-Agents-in-LangGraph
Master the art of building and enhancing AI agents. Learn to develop flow-based applications, implement agentic search, and incorporate human-in-the-loop systems using LangGraph's powerful components.
Carbon-Aware-Computing
Execute tasks on a point in time with minimal grid carbon intensity
AI-Agentic-Design-Patterns-with-AutoGen
Learn to build and customize multi-agent systems using the AutoGen. The course teaches you to implement complex AI applications through agent collaboration and advanced design patterns.
pair
REPL environment for GPT pair programming
KG_RAG
Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks
GAI-Choy
An intelligent coding assistant plugin for Visual Studio Code, empowered by Azure OpenAI (or CodeShell, optionally)
Multi-AI-Agent-Systems-with-crewAI
Automate complex business workflows with our Multi-AI-Agent Systems using crewAI. This framework leverages autonomous, role-specific AI agents to collaboratively perform multi-step tasks, enhancing efficiency and accuracy across various domains. Ideal for applications in resume tailoring, website design, research, customer support, and more.
Quantization-in-Depth
Dive into advanced quantization techniques. Learn to implement and customize linear quantization functions, measure quantization error, and compress model weights using PyTorch for efficient and accessible AI models.
aistudio-copilot-sample
Sample quickstart repo for getting started building an enterprise chat copilot in Azure AI Studio
building-agentic-rag-with-llamaindex
Learn how to build agents that can reason over their own documents
Hands-On-Genetic-Algorithms-with-Python-Second-Edition
Hands-On Genetic Algorithms with Python, Second Edition, published by Packt
Prompt-Engineering-for-Vision-Models
Enhance your skills in prompt engineering for vision models. Learn to effectively prompt, fine-tune, and track experiments for models like SAM, OWL-ViT, and Stable Diffusion 2.0 to achieve precise image generation, segmentation, and object detection.
Advanced_RAG
Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs ,META LLAMA3 , Agents.
Quantization-Fundamentals-with-Hugging-Face
Learn linear quantization techniques using the Quanto library and downcasting methods with the Transformers library to compress and optimize generative AI models effectively.
Vehicle-Digital-Twin-Feedback-Loop
In this repository you'll find everything you need to get started in creating a Digital Twin with MongoDB and AWS. More specifically, you'll find code samples and demos using the Realm database with MongoDB Atlas, Device sync and Amazon SageMaker.
Efficiently-Serving-LLMs
Learn the ins and outs of efficiently serving Large Language Models (LLMs). Dive into optimization techniques, including KV caching and Low Rank Adapters (LoRA), and gain hands-on experience with Predibase’s LoRAX framework inference server.
Wind-Turbine-Diagnostics
Using MongoDB Atlas Vector Search to determine issues with wind turbines
smart-factory-computer-vision-inference
How to connect the camera on a Smart Factory to feed a Computer Vision model in order to sync its Digital Twin