Models without Vocabulary #5798
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cebtenzzre
reviewed
Feb 29, 2024
cebtenzzre
reviewed
Feb 29, 2024
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Do you have a more specific example of a use case for this feature - e.g., a model with a vocab type not currently supported by llama.cpp, but with weights that are? |
ggerganov
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Mar 1, 2024
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@cebtenzzre right now we're using some kind of this tokenizer with the llama model trained by our ml engineers. And in our system the vocab is on the client side, and the server only processes tokens. So there is no need for the vocab to be included in the model. |
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cebtenzzre
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Mar 8, 2024
cebtenzzre
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Mar 12, 2024
cebtenzzre
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Mar 12, 2024
cebtenzzre
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Mar 14, 2024
cebtenzzre
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Mar 14, 2024
NeoZhangJianyu
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Mar 15, 2024
* additional methods to read model and ctx parameters * vocab size as a part of a model metadata * models without vocabulary, convert.py part * models without vocabulary, llama.cpp part * PR clean up * converter scrypt fixes * llama_vocab_type update (renamed the new key) * pr review fixes * revert function renaming * one more NoVocab assert
hodlen
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Apr 1, 2024
* additional methods to read model and ctx parameters * vocab size as a part of a model metadata * models without vocabulary, convert.py part * models without vocabulary, llama.cpp part * PR clean up * converter scrypt fixes * llama_vocab_type update (renamed the new key) * pr review fixes * revert function renaming * one more NoVocab assert
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I made some changes to the model converter so that it could create a gguf model without a built-in dictionary.
This will allow to use any custom external dictionary in an application built with llama.cpp.