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fa79495bb4
* 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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.. | ||
.gitignore | ||
CMakeLists.txt | ||
get-model.cpp | ||
get-model.h | ||
run-json-schema-to-grammar.mjs | ||
test-autorelease.cpp | ||
test-backend-ops.cpp | ||
test-c.c | ||
test-chat-template.cpp | ||
test-double-float.cpp | ||
test-grad0.cpp | ||
test-grammar-integration.cpp | ||
test-grammar-parser.cpp | ||
test-json-schema-to-grammar.cpp | ||
test-llama-grammar.cpp | ||
test-model-load-cancel.cpp | ||
test-opt.cpp | ||
test-quantize-fns.cpp | ||
test-quantize-perf.cpp | ||
test-rope.cpp | ||
test-sampling.cpp | ||
test-tokenizer-0.cpp | ||
test-tokenizer-0.py | ||
test-tokenizer-0.sh | ||
test-tokenizer-1-bpe.cpp | ||
test-tokenizer-1-spm.cpp | ||
test-tokenizer-random.py |