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Support Llama 3 conversion #6745

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merged 8 commits into from
Apr 21, 2024
Merged

Support Llama 3 conversion #6745

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d79ab10
Support Llama 3 conversion
pcuenca Apr 18, 2024
112c4c4
style
pcuenca Apr 18, 2024
f3105b9
Accept suggestion
pcuenca Apr 19, 2024
4b47c24
llama : add llama_token_is_eog()
ggerganov Apr 20, 2024
d0a4cc8
llama : auto-detect more EOT tokens when missing in KV data
ggerganov Apr 21, 2024
7ab0939
convert : replacing EOS token is a hack
ggerganov Apr 21, 2024
23b8dd7
llama : fix codegemma EOT token + add TODOs
ggerganov Apr 21, 2024
c971ac0
llama : fix model type string for 8B model
ggerganov Apr 21, 2024
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26 changes: 17 additions & 9 deletions convert-hf-to-gguf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1301,15 +1301,23 @@ def set_vocab(self):
try:
self. _set_vocab_sentencepiece()
except FileNotFoundError:
self._set_vocab_llama_hf()

special_vocab = gguf.SpecialVocab(self.dir_model, load_merges=False,
special_token_types = ['prefix', 'suffix', 'middle', 'eot'])
special_vocab._set_special_token("prefix", 32007)
special_vocab._set_special_token("suffix", 32008)
special_vocab._set_special_token("middle", 32009)
special_vocab._set_special_token("eot", 32010)
special_vocab.add_to_gguf(self.gguf_writer)
try:
self._set_vocab_llama_hf()
except TypeError:
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# Llama 3
self._set_vocab_gpt2()

# Apply to CodeLlama only (and ignore for Llama 3 with a vocab size of 128256)
if self.hparams.get("vocab_size", 32000) == 32016:
special_vocab = gguf.SpecialVocab(
self.dir_model, load_merges=False,
special_token_types = ['prefix', 'suffix', 'middle', 'eot']
)
special_vocab._set_special_token("prefix", 32007)
special_vocab._set_special_token("suffix", 32008)
special_vocab._set_special_token("middle", 32009)
special_vocab._set_special_token("eot", 32010)
special_vocab.add_to_gguf(self.gguf_writer)

def set_gguf_parameters(self):
super().set_gguf_parameters()
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9 changes: 8 additions & 1 deletion convert.py
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Original file line number Diff line number Diff line change
Expand Up @@ -525,7 +525,14 @@ def __init__(self, base_path: Path):

# pre-check so we know if we need transformers
tokenizer_model: dict[str, Any] = tokenizer_json['model']
if (
is_llama3 = (
tokenizer_model['type'] == 'BPE' and tokenizer_model.get('ignore_merges', False)
and not tokenizer_model.get('byte_fallback', True)
)
if is_llama3:
raise TypeError('Llama 3 must be converted with BpeVocab')

if not is_llama3 and (
tokenizer_model['type'] != 'BPE' or not tokenizer_model.get('byte_fallback', False)
or tokenizer_json['decoder']['type'] != 'Sequence'
):
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