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import torch
class Config:
def __init__(self):
self.image_size: int = 512 # the generated image resolution
self.sample_rate: int = 44100 # the sample rate of the audio
self.guidance_scale: float = 1 # the guidance scale for the diffusion process
self.mixed_precision: str = "fp16" # `no` for float32, `fp16` for automatic mixed precision
self.hub_model_id: str = "alppo/amuse" # the name of the repository to create on the HF Hub
self.hub_dataset_id: str = "alppo/music" # the name of the dataset to create on the HF Hub
self.seed: int = 0
self.device = "cuda" if torch.cuda.is_available() else "cpu"
self.generated_track_path = "new_track.wav"
config = Config() |