Language models and tokenizers#
Language-model training and inference, checkpoints, tokenizers and corpora.
Byte-level BPE tokenizer in the GPT-2 format, over your vocabulary. |
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Dimensions of the decoder language model: batch, sequence, layers, vocabulary. |
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Train and run FP32 decoder language models. |
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Run a trained decoder language model on the CPU, with no GPU. |
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Tokenize a training corpus once and train a language model on the ids. |
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Load and run Hugging Face-format causal language models. |
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FP32 decoder language model trainer (AdamW, mean cross-entropy). |
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Byte-level BPE tokenization with a vocabulary you supply or train. |