Build a GGUF Parser and Safetensors Loader: A From-Scratch Mmap-Backed Weight Inspector
Build a from-scratch GGUF parser and safetensors loader that memory-maps tensor data straight into numpy, with integrity checks you can drop on a CV.
Build a from-scratch GGUF parser and safetensors loader that memory-maps tensor data straight into numpy, with integrity checks you can drop on a CV.
Build a real GGUF parser and tensor loader from scratch in Rust — metadata parsing, q4_0/q8_0 dequantization, mmap’d weight streaming, and a minimal Llama forward pass. The kind of CV project that gets interviews at systems and ML infra teams.
Build a runnable GGUF parser and dequantizer for Q4_K and Q6_K, map the result into a PyTorch Llama model, and end up with a project that signals real ML systems skill on your CV.
Parse GGUF, dequantize Q4_0 and Q8_0 tensors, and load Llama weights into numpy. A hands-on guide to a side project that demonstrates real systems engineering on a CV.
How to ship small language models to local edge devices without falling into the usual latency, memory, or quality traps. Covers quantization, llama.cpp, batching, and the operational metrics that actually matter.