from transformers import PretrainedConfig | |
from typing import List | |
class DeepFakeConfig(PretrainedConfig): | |
model_type = "pulse2pulse" | |
def __init__(self, **kwargs): | |
# if block_type not in ["basic", "bottleneck"]: | |
# raise ValueError(f"`block_type` must be 'basic' or bottleneck', got {block_type}.") | |
# if stem_type not in ["", "deep", "deep-tiered"]: | |
# raise ValueError(f"`stem_type` must be '', 'deep' or 'deep-tiered', got {stem_type}.") | |
super().__init__(**kwargs) |