Fixed n vocab #9511
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Fixed n vocab #9511
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ggerganov
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Sep 16, 2024
ggerganov
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Sep 17, 2024
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Btw, we currently have state duplication in the sense that hparams.n_vocab and vocab.n_vocab are the same thing but initialized independently in different ways. The reason to have the latter is because some parts of the implementation are decoupled from the model/hparams.
Just noting this here for awareness - no action is necessary for this PR. Will be resolved in future refactorings.
Co-authored-by: Georgi Gerganov <[email protected]>
ggerganov
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Sep 17, 2024
dsx1986
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Oct 29, 2024
* llama: fixed n_vocab for `no_vocab` models * llama: updated error output for `llama_decode_internal` and `llama_encode_internal` * llama: log warning if there's no vocab_size in metadata * llama: correct vocab size for logging Co-authored-by: Georgi Gerganov <[email protected]> --------- Co-authored-by: Georgi Gerganov <[email protected]>
arthw
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Nov 15, 2024
* llama: fixed n_vocab for `no_vocab` models * llama: updated error output for `llama_decode_internal` and `llama_encode_internal` * llama: log warning if there's no vocab_size in metadata * llama: correct vocab size for logging Co-authored-by: Georgi Gerganov <[email protected]> --------- Co-authored-by: Georgi Gerganov <[email protected]>
arthw
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Nov 18, 2024
* llama: fixed n_vocab for `no_vocab` models * llama: updated error output for `llama_decode_internal` and `llama_encode_internal` * llama: log warning if there's no vocab_size in metadata * llama: correct vocab size for logging Co-authored-by: Georgi Gerganov <[email protected]> --------- Co-authored-by: Georgi Gerganov <[email protected]>
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For
no_vocabmodels, the currentllm_load_vocabfunction incorrectly fillsn_vocab, which is why anerror occurs during inference.