image-match/python/py/Lib/site-packages/transformers/models/mlcd/configuration_mlcd.py

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#           This file was automatically generated from src/transformers/models/mlcd/modular_mlcd.py.
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# Copyright 2025 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#
#     http://www.apache.org/licenses/LICENSE-2.0
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from huggingface_hub.dataclasses import strict

from ...configuration_utils import PreTrainedConfig
from ...utils import auto_docstring


@auto_docstring(checkpoint="DeepGlint-AI/mlcd-vit-bigG-patch14-336")
@strict
class MLCDVisionConfig(PreTrainedConfig):
    r"""
    num_key_value_groups (`int`, *optional*, defaults to 1):
        Number of key-value groups used in Attention.

    Example:

    ```python
    >>> from transformers import MLCDVisionConfig, MLCDVisionModel

    >>> # Initializing a MLCDVisionConfig with DeepGlint-AI/mlcd-vit-bigG-patch14-336 style configuration
    >>> configuration = MLCDVisionConfig()

    >>> # Initializing a MLCDVisionModel (with random weights) from the DeepGlint-AI/mlcd-vit-bigG-patch14-336 style configuration
    >>> model = MLCDVisionModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```"""

    model_type = "mlcd_vision_model"
    base_config_key = "vision_config"

    hidden_size: int = 1664
    intermediate_size: int = 8192
    num_hidden_layers: int = 48
    num_attention_heads: int = 16
    num_key_value_groups: int = 1
    num_channels: int = 3
    image_size: int | list[int] | tuple[int, int] = 336
    patch_size: int | list[int] | tuple[int, int] = 14
    hidden_act: str = "gelu"
    layer_norm_eps: float = 1e-5
    attention_dropout: float | int = 0.0
    initializer_range: float = 0.02
    initializer_factor: float = 1.0


__all__ = ["MLCDVisionConfig"]