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Fix hang in tokenizer for AutoGPTQ llama models. (#2399)

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Forkoz 2023-05-28 21:10:10 -05:00 • committed by GitHub
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modules/models.py
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@ -114,7 +114,7 @@ def load_tokenizer(model_name, model):
tokenizer = None tokenizer = None
if shared.model_type == 'gpt4chan' and Path(f"{shared.args.model_dir}/gpt-j-6B/").exists(): if shared.model_type == 'gpt4chan' and Path(f"{shared.args.model_dir}/gpt-j-6B/").exists():
tokenizer = AutoTokenizer.from_pretrained(Path(f"{shared.args.model_dir}/gpt-j-6B/")) tokenizer = AutoTokenizer.from_pretrained(Path(f"{shared.args.model_dir}/gpt-j-6B/"))
elif type(model) is transformers.LlamaForCausalLM: elif type(model) is transformers.LlamaForCausalLM or "LlamaGPTQForCausalLM" in str(type(model)):
# Try to load an universal LLaMA tokenizer # Try to load an universal LLaMA tokenizer
if shared.model_type not in ['llava', 'oasst']: if shared.model_type not in ['llava', 'oasst']:
for p in [Path(f"{shared.args.model_dir}/llama-tokenizer/"), Path(f"{shared.args.model_dir}/oobabooga_llama-tokenizer/")]: for p in [Path(f"{shared.args.model_dir}/llama-tokenizer/"), Path(f"{shared.args.model_dir}/oobabooga_llama-tokenizer/")]: