s2s / arguments_classes /parler_tts_arguments.py
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from dataclasses import dataclass, field
@dataclass
class ParlerTTSHandlerArguments:
tts_model_name: str = field(
default="ylacombe/parler-tts-mini-jenny-30H",
metadata={
"help": "The pretrained TTS model to use. Default is 'ylacombe/parler-tts-mini-jenny-30H'."
},
)
tts_device: str = field(
default="cuda",
metadata={
"help": "The device type on which the model will run. Default is 'cuda' for GPU acceleration."
},
)
tts_torch_dtype: str = field(
default="float16",
metadata={
"help": "The PyTorch data type for the model and input tensors. One of `float32` (full-precision), `float16` or `bfloat16` (both half-precision)."
},
)
tts_compile_mode: str = field(
default=None,
metadata={
"help": "Compile mode for torch compile. Either 'default', 'reduce-overhead' and 'max-autotune'. Default is None (no compilation)"
},
)
tts_gen_min_new_tokens: int = field(
default=64,
metadata={
"help": "Maximum number of new tokens to generate in a single completion. Default is 10, which corresponds to ~0.1 secs"
},
)
tts_gen_max_new_tokens: int = field(
default=512,
metadata={
"help": "Maximum number of new tokens to generate in a single completion. Default is 256, which corresponds to ~6 secs"
},
)
description: str = field(
default=(
"A female speaker with a slightly low-pitched voice delivers her words quite expressively, in a very confined sounding environment with clear audio quality. "
"She speaks very fast."
),
metadata={
"help": "Description of the speaker's voice and speaking style to guide the TTS model."
},
)
play_steps_s: float = field(
default=1.0,
metadata={
"help": "The time interval in seconds for playing back the generated speech in steps. Default is 0.5 seconds."
},
)
max_prompt_pad_length: int = field(
default=8,
metadata={
"help": "When using compilation, the prompt as to be padded to closest power of 2. This parameters sets the maximun power of 2 possible."
},
)