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Add universal LLaMA tokenizer support

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oobabooga 2023-04-19 21:23:51 -03:00
parent 32d47e4bad
commit 7bb9036ac9
1 changed files with 19 additions and 9 deletions
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28
modules/models.py
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@ -193,15 +193,25 @@ def load_model(model_name):
if any((k in shared.model_name.lower() for k in ['gpt4chan', 'gpt-4chan'])) and Path(f"{shared.args.model_dir}/gpt-j-6B/").exists():
tokenizer = AutoTokenizer.from_pretrained(Path(f"{shared.args.model_dir}/gpt-j-6B/"))
elif type(model) is transformers.LlamaForCausalLM:
tokenizer = LlamaTokenizer.from_pretrained(Path(f"{shared.args.model_dir}/{shared.model_name}/"), clean_up_tokenization_spaces=True)
# Leaving this here until the LLaMA tokenizer gets figured out.
# For some people this fixes things, for others it causes an error.
try:
tokenizer.eos_token_id = 2
tokenizer.bos_token_id = 1
tokenizer.pad_token_id = 0
except:
pass
tokenizer = None
# Try to load an universal LLaMA tokenizer
for p in [Path(f"{shared.args.model_dir}/llama-tokenizer/"), Path(f"{shared.args.model_dir}/oobabooga_llama-tokenizer/")]:
if p.exists():
print(f"Loading the universal LLaMA tokenizer from {p}...")
tokenizer = LlamaTokenizer.from_pretrained(p, clean_up_tokenization_spaces=True)
break
# Otherwise, load it from the model folder and hope that these
# are not outdated tokenizer files.
if tokenizer is None:
tokenizer = LlamaTokenizer.from_pretrained(Path(f"{shared.args.model_dir}/{shared.model_name}/"), clean_up_tokenization_spaces=True)
try:
tokenizer.eos_token_id = 2
tokenizer.bos_token_id = 1
tokenizer.pad_token_id = 0
except:
pass
else:
tokenizer = AutoTokenizer.from_pretrained(Path(f"{shared.args.model_dir}/{shared.model_name}/"), trust_remote_code=trust_remote_code)