Training a Language Model End-to-End in Rust: An Experience Report
An experience report on training a language model in Rust and the encountered issues.
I pretrained a language model end-to-end in Rust, alone, without a team or Python involvement. This report highlights a failure taxonomy of two leading Rust ML frameworks, Candle and Burn, documenting several defects that went unnoticed during training. The findings suggest that while Rust may not yet be suitable for training language models, it shows promise for serving them.
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