Fix converter for internlm2 #8321
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compilade
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| # take care of ununsed raw token | ||
| if piece.startswith('[UNUSED'): | ||
| toktype = SentencePieceTokenTypes.UNKNOWN |
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I wonder, does it work without this if the checks for UNKNOWN below are replaced with checks for UNUSED?
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hi, these raw tokens are in fact used and updated by added_tokens_decoder. And there are asserations in line 2180 and 2199 which is aligned with what's done in phi3. The tokens are all read as SentencePieceTokenTypes.NORMAL and the assertations would fail if remove or change to UNUSED type.
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This makes the changes from #8321 more consistent with the other changes made here.
arthw
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* update internlm2 * remove unused file * fix lint
arthw
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* update internlm2 * remove unused file * fix lint
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* llama : fix mpt and olmo pre-tokenizer * llama : pre-tokenize non-special user-defined tokens first * llama : fix detection of control-like user-defined tokens * convert_hf : identify which user-defined tokens are control tokens Only used in _set_vocab_gpt2() for now. * convert_hf : identify more added control tokens for SPM tokenziers This makes Gemma and Gemma-2 tokenize pretty much EVERYTHING correctly, including HTML tags and consecutive spaces, but it unfortunately requires model re-conversion. There seems to be a weird behavior of the HF tokenizer for Gemma, which prefers to use the 16-space token over more lengthy space tokens, while using the SentencePiece tokenizer does not do this. (the implementation in llama.cpp has the same behavior as SentencePiece) * llama : fix wrong pre-tokenization of byte tokens * llama : fix Viking pre-tokenizer regex The order was previously wrong, which caused errors in some tests. * llama : fix command-r detokenization * convert_hf : reduce usages of the UNKNOWN token type * llama : add UNKNOWN tokens in the special tokens cache * convert_hf : reduce usages of UNKNOWN for InternLM2 This makes the changes from #8321 more consistent with the other changes made here. * test-tokenizer-random : reduce potential confilcts with #8379 * test-tokenizer-random : add a failing edge case for falcon
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) * llama : fix mpt and olmo pre-tokenizer * llama : pre-tokenize non-special user-defined tokens first * llama : fix detection of control-like user-defined tokens * convert_hf : identify which user-defined tokens are control tokens Only used in _set_vocab_gpt2() for now. * convert_hf : identify more added control tokens for SPM tokenziers This makes Gemma and Gemma-2 tokenize pretty much EVERYTHING correctly, including HTML tags and consecutive spaces, but it unfortunately requires model re-conversion. There seems to be a weird behavior of the HF tokenizer for Gemma, which prefers to use the 16-space token over more lengthy space tokens, while using the SentencePiece tokenizer does not do this. (the implementation in llama.cpp has the same behavior as SentencePiece) * llama : fix wrong pre-tokenization of byte tokens * llama : fix Viking pre-tokenizer regex The order was previously wrong, which caused errors in some tests. * llama : fix command-r detokenization * convert_hf : reduce usages of the UNKNOWN token type * llama : add UNKNOWN tokens in the special tokens cache * convert_hf : reduce usages of UNKNOWN for InternLM2 This makes the changes from ggerganov#8321 more consistent with the other changes made here. * test-tokenizer-random : reduce potential confilcts with ggerganov#8379 * test-tokenizer-random : add a failing edge case for falcon
arthw
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Jul 27, 2024
) * llama : fix mpt and olmo pre-tokenizer * llama : pre-tokenize non-special user-defined tokens first * llama : fix detection of control-like user-defined tokens * convert_hf : identify which user-defined tokens are control tokens Only used in _set_vocab_gpt2() for now. * convert_hf : identify more added control tokens for SPM tokenziers This makes Gemma and Gemma-2 tokenize pretty much EVERYTHING correctly, including HTML tags and consecutive spaces, but it unfortunately requires model re-conversion. There seems to be a weird behavior of the HF tokenizer for Gemma, which prefers to use the 16-space token over more lengthy space tokens, while using the SentencePiece tokenizer does not do this. (the implementation in llama.cpp has the same behavior as SentencePiece) * llama : fix wrong pre-tokenization of byte tokens * llama : fix Viking pre-tokenizer regex The order was previously wrong, which caused errors in some tests. * llama : fix command-r detokenization * convert_hf : reduce usages of the UNKNOWN token type * llama : add UNKNOWN tokens in the special tokens cache * convert_hf : reduce usages of UNKNOWN for InternLM2 This makes the changes from ggerganov#8321 more consistent with the other changes made here. * test-tokenizer-random : reduce potential confilcts with ggerganov#8379 * test-tokenizer-random : add a failing edge case for falcon
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fix internlm2 gguf output eos token at the end of each conversation
output example: