llm.c
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Llm.c
Overview :
karpathy/llm.c is a project that implements LLM training using a simple C/CUDA implementation. It aims to provide a clean and straightforward reference implementation while also including optimized versions that can approach the performance of PyTorch with drastically reduced code and dependencies. It is currently under development for a direct CUDA implementation, CPU version optimization using SIMD instructions, and support for more modern architectures such as Llama2 and Gemma.
Target Users :
Serves as a reference implementation for LLM training and a foundation for further optimization and expansion of LLM models.
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Use Cases
Implemented a small-scale language model based on GPT-2 using karpathy/llm.c and achieved significant speed improvements through the optimized version.
Developed an LLM training tool that supports the Llama2 architecture based on karpathy/llm.c.
Referred to the code structure and implementation of karpathy/llm.c to develop a custom LLM model tailored to a specific application scenario.
Features
Uses simple C/CUDA to implement LLM training
Provides a clean and simple reference implementation
Includes optimized versions with performance close to PyTorch
Supports various modern LLM architectures
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