During the phase of trainingi vari LLM (Large Language Model) – now commonly used in artificial intelligence applications – learn a series of numerical parameters essential for their correct functioning. These parameters are called weights.
An LLM is in fact built using deep neural networks (deep neural network). These networks are organized into layers (layer), each composed of interconnected nodes. Weights are the parameters that regulate the “intensity” and direction of the connections between the nodes in the various layers that make up the model.
During the training phase, the model is fed a huge volume of linguistic data, such as texts and sentences. The goal is to induce the model to establish the relationships between words and arrive at composing interconnections that have their roots in an essentially probabilistic approach.
The weights of an LLM encode the “knowledge” acquired during training. They can therefore represent the semantic relationships between words, grammatical regularities and other complex aspects of language. By changing the weights, the model can adapt to a wide range of linguistic tasks.
Mozilla transforms the weights of an LLM into an executable file with llamafile
The research and development group of Mozilla released and published a very interesting project on GitHub. Is called llamafile: allows you to manage and transform LLM weights into executables, so as to make them directly usable on different platforms. With this approach, Mozilla facilitates distribution andrunning the models without the need for complex installation.
LLM weights are generally stored in a file several gigabytes in size GGUF format. llamafile is presented as a revolutionary tool that transforms weights into a binary executable usable on 6 different operating systems (macOS, Windows, Linux, FreeBSD, OpenBSD and NetBSD): it is sufficient compile the code only once.
The “engine” that makes magic possible is called Cosmopolitan Libc: This is an open source project that facilitates compilation and the execution of C programs across a wide range of platforms and architectures. This ensures that the generated binary file is compatible with various operating systems.
The key features of llamafile
With the whirlwind evolution of language models and their weights that we are witnessing, llamafile provides a solution to maintain theusability and the consistency in time. The project is released under the license Apache 2.0encouraging community contribution and allowing any type of use.
The goal of llamafile is to make the dream come true “build once anywhere, run anywhere” for developers of solutions based onartificial intelligencecombining call.cpp con Cosmopolitan Libc in a single framework. Call.cpp is a C/C++ implementation of Meta LLaMa, an LLM capable of generating text, processing translations, summaries and performing other tasks related to natural language.
The solution proposed by Mozilla was created to guarantee maximum microarchitectural compatibility at the CPU level. Furthermore, llamafile executables can be used on both AMD64 and ARM64 platforms. On the slope GPU, llamafile supports both NVidia cards and Apple Silicon-based solutions. LLM weights can be embedded directly into the file, supporting PKZIP compression.
Examples of llamafiles ready for download
On the llamafile GitHub page, Mozilla provides examples of binary files which incorporate different models. There are both command-line exploitable files and binaries that can launch a local web server to serve a chatbot web-based.
Developers and researchers can of course also download just the llamafile software (without weights) from the download page or directly from the terminal window.
Opening image credit: iStock.com/BlackJack3D