YaLM 100B is a GPT-like neural network for generating and processing text. It can be used freely by developers and researchers from all over the world.
The model leverages 100 billion parameters. It took 65 days to train the model on a cluster of 800 A100 graphics cards and 1.7 TB of online texts, books, and countless other sources in both English and Russian.
Training details and best practices on acceleration and stabilizations can be found on Medium (English) and Habr (Russian) articles.
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Looks like you need around 200GB in GPU to get it to run…