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Various changes
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@ -1,4 +0,0 @@
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user: "### Human:"
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bot: "### Assistant:"
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turn_template: "<|user|><|user-message|>\n<|bot|><|bot-message|>\n"
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context: "A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.\n\n"
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@ -240,6 +240,6 @@ TheBloke_WizardLM-30B-GPTQ:
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truncation_length: 8192
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.*superhot-8k:
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truncation_length: 8192
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.*xgen:
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.*xgen.*-inst:
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truncation_length: 8192
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instruction_template: 'XGen'
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instruction_template: 'Vicuna-v0'
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@ -94,8 +94,6 @@ def load_tokenizer(model_name, model):
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if any(s in model_name.lower() for s in ['gpt-4chan', 'gpt4chan']) and Path(f"{shared.args.model_dir}/gpt-j-6B/").exists():
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tokenizer = AutoTokenizer.from_pretrained(Path(f"{shared.args.model_dir}/gpt-j-6B/"))
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elif model.__class__.__name__ in ['LlamaForCausalLM', 'LlamaGPTQForCausalLM', 'ExllamaHF']:
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if any(s in model_name.lower() for s in ['xgen']) and Path(f"{shared.args.model_dir}/{model_name}/").exists():
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tokenizer = AutoTokenizer.from_pretrained(Path(f"{shared.args.model_dir}/{model_name}/"), trust_remote_code=shared.args.trust_remote_code)
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# Try to load an universal LLaMA tokenizer
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if not any(s in shared.model_name.lower() for s in ['llava', 'oasst']):
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for p in [Path(f"{shared.args.model_dir}/llama-tokenizer/"), Path(f"{shared.args.model_dir}/oobabooga_llama-tokenizer/")]:
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