fastchat/model/model_adapter.py [1458:1472]:
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        )

    def load_model(self, model_path: str, from_pretrained_kwargs: dict):
        revision = from_pretrained_kwargs.get("revision", "main")
        tokenizer = AutoTokenizer.from_pretrained(
            model_path, use_fast=self.use_fast_tokenizer, revision=revision
        )
        model = AutoModelForCausalLM.from_pretrained(
            model_path,
            low_cpu_mem_usage=True,
            **from_pretrained_kwargs,
        ).eval()
        return model, tokenizer

    def get_default_conv_template(self, model_path: str) -> Conversation:
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fastchat/model/model_adapter.py [1487:1501]:
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        )

    def load_model(self, model_path: str, from_pretrained_kwargs: dict):
        revision = from_pretrained_kwargs.get("revision", "main")
        tokenizer = AutoTokenizer.from_pretrained(
            model_path, use_fast=self.use_fast_tokenizer, revision=revision
        )
        model = AutoModelForCausalLM.from_pretrained(
            model_path,
            low_cpu_mem_usage=True,
            **from_pretrained_kwargs,
        ).eval()
        return model, tokenizer

    def get_default_conv_template(self, model_path: str) -> Conversation:
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