#GGUF

The gguf-tools library facilitates the manipulation and documentation of GGUF files, essential in the local machine learning landscape. The tools include utilities for displaying detailed GGUF information, analyzing tensor differences between models, and examining tensor weights. Although in active development, the project provides real-world applications, with experimental features still under refinement. While user-friendly and well-documented, its current limitations include missing quantization formats. Discover its potential applications in 'llama.cpp' and other machine learning projects.

Explore an effective toolkit for air-gapped LLMs featuring LangChain and Qdrant. It supports local data processing and query handling without internet requirement, facilitating diverse dataset ingestion and robust GUI interaction. Includes GPU support and model conversion from GGML for optimal use.