53 lines
2.1 KiB
Python
53 lines
2.1 KiB
Python
from typing import Optional
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from transformers import AutoConfig, PretrainedConfig
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from vllm.transformers_utils.configs import *
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_CONFIG_REGISTRY = {
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"chatglm": ChatGLMConfig,
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"mpt": MPTConfig,
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"RefinedWeb": RWConfig, # For tiiuae/falcon-40b(-instruct)
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"RefinedWebModel": RWConfig, # For tiiuae/falcon-7b(-instruct)
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"starcoder2": Starcoder2Config,
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"minicpm": CPMDragonflyConfig,
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}
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def get_config(model: str,
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trust_remote_code: bool,
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revision: Optional[str] = None,
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code_revision: Optional[str] = None) -> PretrainedConfig:
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# FIXME(woosuk): This is a temporary fix for StarCoder2.
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# Remove this when the model is supported by HuggingFace transformers.
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if "bigcode" in model and "starcoder2" in model:
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config_class = _CONFIG_REGISTRY["starcoder2"]
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config = config_class.from_pretrained(model,
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revision=revision,
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code_revision=code_revision)
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return config
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try:
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config = AutoConfig.from_pretrained(
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model,
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trust_remote_code=trust_remote_code,
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revision=revision,
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code_revision=code_revision)
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except ValueError as e:
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if (not trust_remote_code and
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"requires you to execute the configuration file" in str(e)):
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err_msg = (
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"Failed to load the model config. If the model is a custom "
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"model not yet available in the HuggingFace transformers "
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"library, consider setting `trust_remote_code=True` in LLM "
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"or using the `--trust-remote-code` flag in the CLI.")
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raise RuntimeError(err_msg) from e
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else:
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raise e
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if config.model_type in _CONFIG_REGISTRY:
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config_class = _CONFIG_REGISTRY[config.model_type]
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config = config_class.from_pretrained(model,
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revision=revision,
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code_revision=code_revision)
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return config
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