chunked/nltk_chunking/_custom_models/chunk_14.txt

thon
from transformers import PretrainedConfig
from typing import List
class ResnetConfig(PretrainedConfig):
    model_type = "resnet"
def __init__(
    self,
    block_type="bottleneck",
    layers: List[int] = [3, 4, 6, 3],
    num_classes: int = 1000,
    input_channels: int = 3,
    cardinality: int = 1,
    base_width: int = 64,
    stem_width: int = 64,
    stem_type: str = "",
    avg_down: bool = False,
    **kwargs,
):
    if block_type not in ["basic", "bottleneck"]:
        raise ValueError(f"`block_type` must be 'basic' or bottleneck', got {block_type}.")