tutorial

voice cloning

Build a Local AI Voice Cloning Studio in Telegram

A hands-on guide to turning Telegram into a private, local AI voice studio—combining text-to-speech and voice cloning models that run on your own hardware, no cloud APIs required.

LLM Training

Training GPT-Style Models on a GTX 1050: Lessons Learned

A hands-on exploration of training GPT-style transformer models on a budget GTX 1050 GPU, revealing practical constraints, optimization tricks, and what hobbyists can realistically achieve with limited VRAM.

LLM

Running PrismML Bonsai 1-Bit LLM on CUDA with GGUF & RAG

A technical walkthrough of deploying PrismML's Bonsai 1-bit LLM on CUDA using GGUF quantization, with benchmarking, structured JSON output, chat, and retrieval-augmented generation pipelines.

LLM

Building Type-Safe LLM Pipelines with Outlines and Pydantic

Learn how to build reliable LLM pipelines with guaranteed structured outputs using the Outlines library and Pydantic schemas for type-safe AI applications.

AI Infrastructure

AI Model Hosting Guide: Local and Cloud Inference Strategies

Master the essentials of deploying AI models for efficient inference. This guide covers local hosting, cloud deployment options, and optimization strategies for production-ready AI systems.

AI Agents

Building AI Agents From Scratch: Beyond Framework Abstractions

Learn to construct AI agents using raw Python and API calls, understanding the core patterns that LangChain abstracts away for better control and debugging.

Multi-Agent AI

Multi-Agent AI Systems: CrewAI, LangGraph & Docker Guide

A comprehensive technical guide to building production-ready multi-agent AI systems using CrewAI for agent orchestration, LangGraph for workflow graphs, FastAPI for APIs, and Docker for deployment.

LLM

Master LLM Fine-Tuning: LoRA, QLoRA, and PEFT Explained

A comprehensive guide to fine-tuning large language models using parameter-efficient techniques like LoRA and QLoRA, from fundamentals to production deployment.

GPT

Training GPT Models on MacBook Air M1: A Technical Guide

A detailed technical walkthrough of training transformer-based language models on consumer hardware, covering tokenization, architecture implementation, training optimization, and resource management on Apple Silicon.

Transformers

Building Transformers from Scratch with Tinygrad

Learn to implement transformer components and mini-GPT models from the ground up using Tinygrad. This technical deep dive covers attention mechanisms, layer normalization, and neural network fundamentals to understand how modern AI systems work.

multimodal-AI

Building Multimodal AI Assistants with Vision and Audio

Learn to build AI assistants that process images and audio using Hugging Face models. Technical guide covers vision transformers, audio processing, and LLM integration with practical implementation steps.

LLM

Build Custom GPT Conversational AI Locally with Hugging Face

A comprehensive technical guide to building GPT-style conversational AI systems locally using Hugging Face Transformers, covering model selection, memory optimization, and deployment strategies for privacy-focused implementations.