Building a GGUF Parser with Memory-Mapped Lazy Tensor Loading in Pure Python
A hands-on guide to building a pure-Python GGUF parser that lazily memory-maps tensors and decompresses quantized blocks on demand, demonstrating deep systems knowledge.
Gguf
Hands‑On: Building a Zero‑Dependency Pure‑Python GGUF Model Loader with Memory‑Mapped Tensor Access
A lightweight, dependency‑free Python loader for GGUF models that uses memory‑mapped files and on‑the‑fly dtype conversion, perfect for a standout CV project.
Lazy GGUF/Safetensors Checkpoint Loader: A Hands-On Build Guide
A practical guide to building a lazy checkpoint loader that memory-maps GGUF and safetensors files, parses tensor metadata, and dequantizes on demand.
Build a GGUF Parser with Memory-Mapped Quantized Tensor Loading in Pure Python
Build a production-grade GGUF parser from scratch in pure Python, featuring memory-mapped quantized tensor loading. Learn the format internals, write real dequantization kernels, and discover why this project stands out to hiring managers.
Building a Pure-Python GGUF Weight Loader with Dequantization for Llama Models
A hands-on guide to building a pure-Python GGUF weight loader with full dequantization support for Llama models — covering binary parsing, quantized tensor reconstruction, and a roadmap to production-grade infrastructure.