44 lines
1.7 KiB
Python
44 lines
1.7 KiB
Python
from dataclasses import dataclass, field
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from speech_to_speech.arguments_classes.language_model_base_arguments import LanguageModelBaseArguments
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@dataclass
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class LanguageModelHandlerArguments(LanguageModelBaseArguments):
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llm_device: str = field(
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default="cuda",
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metadata={"help": "The device type on which the model will run. Default is 'cuda' for GPU acceleration."},
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)
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llm_torch_dtype: str = field(
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default="float16",
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metadata={
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"help": "The PyTorch data type for the model and input tensors. One of `float32` (full-precision), `float16` or `bfloat16` (both half-precision)."
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},
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)
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llm_gen_max_new_tokens: int = field(
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default=1024,
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metadata={"help": "Maximum number of new tokens to generate in a single completion. Default is 1024."},
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)
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llm_gen_min_new_tokens: int = field(
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default=0,
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metadata={"help": "Minimum number of new tokens to generate in a single completion. Default is 0."},
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)
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llm_gen_temperature: float = field(
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default=0.0,
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metadata={
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"help": "Controls the randomness of the output. Set to 0.0 for deterministic (repeatable) outputs. Default is 0.0."
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},
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)
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llm_gen_do_sample: bool = field(
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default=False,
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metadata={"help": "Whether to use sampling; set this to False for deterministic outputs. Default is False."},
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)
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llm_is_vlm: bool = field(
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default=False,
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metadata={
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"help": "Set to True when using a Vision Language Model (VLM) that accepts image inputs. "
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"Loads AutoProcessor + AutoModelForImageTextToText instead of the default text-only model. "
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"Default is False."
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},
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)
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