Review/Check GGUF files and estimate the memory usage and maximum tokens per second.

A Javascript library (with Typescript types) to parse metadata of GGML based GGUF files.

llama.cpp gguf file parser for javascript

A small utility library for parsing GGUF file info

GGUF parser in Python

a GGUF file parser

GGUF parser for Go

print_gguf.py is a simple utility to parse the header & tensor_infos of GGUF file.

Instantly determines if your computer can run specific LLMs by analyzing hardware specs against real-time Hugging Face data. Features AI-powered spec parsing, neural performance scoring, and expert inference recommendations (GGUF/AWQ/vLLM).

Python package for parsing GGUF files

L-BOM is a small Python CLI that inspects local LLM model artifacts such as .gguf and .safetensors files and emits a lightweight Software Bill of Materials (SBOM) with file identity, format details, model metadata, and parsing warnings.

A Rust library and CLI for parsing GGUF model file headers — extract metadata, architecture, quantization, and tensor info without loading weights.

A gguf parser for cpp

Estimate VRAM/RAM requirements for GGUF models using `gguf-parser`.

A Dart library for parsing GGUF (GPT-Generated Unified Format) model files

GGUF file parser

A GGUF parser.

GGUF format parser

No description available

Elixir GGUF parser

No description available

No description available

GGUF file metadata parser

GGUF v3 format parser for Zig

Parse GGUF file with python

PoC for GGML_PAD integer overflow vulnerability in GGUF parser

A parser for the GGUF file format. Done using swift-binary-parsing.

Post-mortem experiment running llama.cpp on legacy hardware, documenting GGUF/GBNF failures (parser, OOM, SIGILL).

A Python tool that parses local Ollama model blobs to generate a detailed, offline HTML dashboard. Inspect GGUF metadata, chat templates, and parameters hidden inside hash files.

RAG pipeline using LlamaParse, LangChain, Chroma, and Llama.cpp to parse PDFs, generate embeddings, retrieve relevant chunks, and answer questions locally using the LLaMA-Sentient-3B GGUF model.