Karpathy: Let's reproduce GPT-2 (1.6B): one 8XH100 node 24h $672 in llm.c
The GitHub repository focuses on the "llm.c" project by Andrej Karpathy, aiming to implement Large Language Models in C/CUDA without extensive libraries. It emphasizes pretraining GPT-2 and GPT-3 models.
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The GitHub repository at the provided URL pertains to the "llm.c" project led by Andrej Karpathy. It is dedicated to implementing Large Language Models (LLMs) using simple, pure C/CUDA without relying on extensive libraries like PyTorch or cPython. The primary focus of the project lies in pretraining, particularly in replicating models such as GPT-2 and GPT-3. Within the repository, you can find guidance on reproducing the GPT-2 model, running the code on a single GPU with fp32, CPU execution instructions, available datasets, testing protocols, tutorials, multi-GPU and multi-node training methods, experiments/sweeps, notable forks in various languages, discussions, and licensing details. For further insights or support regarding this initiative, users are encouraged to delve deeper into the repository or seek assistance in the Discussions section of the GitHub platform.
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7 commentsWhat I think will be interesting is when commodity hardware can run cheap inference from very capable, specialized models. Pretty sure it will spawn a new golden age of AI-powered desktop applications.
For example, video game space has already been trying to create AI-powered NPCs, world generation and story-telling (e.g. Inworld AI).
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