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llama : fix mpt and olmo pre-tokenizer

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This commit is contained in:
Francis Couture-Harpin 2024-06-30 14:34:55 -04:00
parent 1c5eba6f8e
commit db2ffd519d
1 changed files with 28 additions and 7 deletions
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35
src/llama.cpp
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@ -5170,6 +5170,28 @@ static void llm_load_vocab(
vocab.token_to_id[word] = i; vocab.token_to_id[word] = i;
vocab.max_token_len = std::max(vocab.max_token_len, (int) word.size()); vocab.max_token_len = std::max(vocab.max_token_len, (int) word.size());
// TODO: properly handle pre-normalized added_tokens and remove this
// handle space tokens with dual tokens,
// like the pre-normalized added_tokens
// of neox-style tokenizers (mpt, olmo, stablelm, etc)
if (word.find(' ') != std::string::npos) {
// same as in the internal `unicode_byte_encoding_process`
// TODO: extract and expose this in some unicode_* function
std::string text_utf;
auto utf_word = unicode_cpts_from_utf8(word);
for (size_t i = 0; i < utf_word.size(); ++i) {
text_utf += unicode_cpt_to_utf8(utf_word[i]);
}
std::string encoded_token;
for (char & c : text_utf) {
encoded_token += unicode_byte_to_utf8(c);
}
// override token id
vocab.token_to_id[encoded_token] = i;
}
auto & token_data = vocab.id_to_token[i]; auto & token_data = vocab.id_to_token[i];
token_data.text = std::move(word); token_data.text = std::move(word);
token_data.score = scores ? scores[i] : 0.0f; token_data.score = scores ? scores[i] : 0.0f;
@ -13890,13 +13912,9 @@ struct llm_tokenizer_bpe {
}; };
break; break;
case LLAMA_VOCAB_PRE_TYPE_MPT: case LLAMA_VOCAB_PRE_TYPE_MPT:
// TODO: MPT pre-tokenization regexes are unknown case LLAMA_VOCAB_PRE_TYPE_OLMO:
// the following are close, but not exact. run the following:
// ./bin/test-tokenizer-0 ../models/ggml-vocab-mpt.gguf
GGML_ASSERT("MPT pre-tokenization regexes are unknown - fixes needed");
regex_exprs = { regex_exprs = {
"\\s?\\p{L}+", "[ ]{2,24}", // the spaces from the added_tokens are split separately
"\\s?\\p{P}+",
"'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)", "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
}; };
break; break;
@ -13909,7 +13927,6 @@ struct llm_tokenizer_bpe {
}; };
break; break;
case LLAMA_VOCAB_PRE_TYPE_GPT2: case LLAMA_VOCAB_PRE_TYPE_GPT2:
case LLAMA_VOCAB_PRE_TYPE_OLMO:
regex_exprs = { regex_exprs = {
"'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)", "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
}; };
@ -13985,6 +14002,10 @@ struct llm_tokenizer_bpe {
void tokenize(const std::string & text, std::vector<llama_vocab::id> & output) { void tokenize(const std::string & text, std::vector<llama_vocab::id> & output) {
int final_prev_index = -1; int final_prev_index = -1;
// FIXME: pre-tokenize added_tokens (user-defined tokens) before other pre-tokenization
// ref: https://github.com/huggingface/tokenizers/blob/fdd26ba9a3f0c133427aab0423888cbde91362d7/tokenizers/src/tokenizer/mod.rs#L726
// (useful for neox-style tokenizers)
const auto word_collection = unicode_regex_split(text, regex_exprs); const auto word_collection = unicode_regex_split(text, regex_exprs);
symbols_final.clear(); symbols_final.clear();