Search results
Results From The WOW.Com Content Network
Llama (Large Language Model Meta AI, formerly stylized as LLaMA) is a family of large language models (LLMs) released by Meta AI starting in February 2023. [2] [3] The latest version is Llama 3.3, released in December 2024. [4] Llama models are trained at different parameter sizes, ranging between 1B and 405B. [5]
llama.cpp is an open source software library that performs inference on various large language models such as Llama. [3] It is co-developed alongside the GGML project ...
It has 7B and 67B parameters in both Base and Chat forms. The accompanying paper claimed benchmark results higher than most open source LLMs at the time, especially Llama 2. [30]: section 5 The model code was under MIT license, with DeepSeek license for the model itself. [48] The architecture was essentially the same as the Llama series.
The caller cleans the stack after the function call returns. The cdecl calling convention is usually the default calling convention for x86 C compilers, although many compilers provide options to automatically change the calling conventions used. To manually define a function to be cdecl, some support the following syntax:
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.
In computer science, a call stack is a stack data structure that stores information about the active subroutines of a computer program.This type of stack is also known as an execution stack, program stack, control stack, run-time stack, or machine stack, and is often shortened to simply the "stack".
The ARM calling convention mandates using a full-descending stack. In addition, the stack pointer must always be 4-byte aligned, and must always be 8-byte aligned at a function call with a public interface. [3] This calling convention causes a "typical" ARM subroutine to:
The term closure is often used as a synonym for anonymous function, though strictly, an anonymous function is a function literal without a name, while a closure is an instance of a function, a value, whose non-local variables have been bound either to values or to storage locations (depending on the language; see the lexical environment section below).