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config.json

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+{
+  "_name_or_path": "checkpoints/aimv2-large-patch14-224/",
+  "architectures": [
+    "AIMv2Model"
+  ],
+  "attention_dropout": 0.0,
+  "auto_map": {
+    "AutoConfig": "configuration_aimv2.AIMv2Config",
+    "AutoModel": "modeling_aimv2.AIMv2Model",
+    "FlaxAutoModel": "modeling_flax_aimv2.FlaxAIMv2Model"
+  },
+  "hidden_size": 1024,
+  "image_size": 224,
+  "intermediate_size": 2816,
+  "model_type": "aimv2",
+  "num_attention_heads": 8,
+  "num_channels": 3,
+  "num_hidden_layers": 24,
+  "patch_size": 14,
+  "projection_dropout": 0.0,
+  "qkv_bias": false,
+  "rms_norm_eps": 1e-05,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.47.1",
+  "use_bias": false
+}

configuration_aimv2.py

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+from typing import Any
+
+from transformers.configuration_utils import PretrainedConfig
+
+__all__ = ["AIMv2Config"]
+
+
+class AIMv2Config(PretrainedConfig):
+    """This is the configuration class to store the configuration of an [`AIMv2Model`].
+
+    Instantiating a configuration with the defaults will yield a similar configuration
+    to that of the [apple/aimv2-large-patch14-224](https://huggingface.co/apple/aimv2-large-patch14-224).
+
+    Args:
+        hidden_size: Dimension of the hidden representations.
+        intermediate_size: Dimension of the SwiGLU representations.
+        num_hidden_layers: Number of hidden layers in the Transformer.
+        num_attention_heads: Number of attention heads for each attention layer
+            in the Transformer.
+        num_channels: Number of input channels.
+        image_size: Image size.
+        patch_size: Patch size.
+        rms_norm_eps: Epsilon value used for the RMS normalization layer.
+        attention_dropout: Dropout ratio for attention probabilities.
+        projection_dropout: Dropout ratio for the projection layer after the attention.
+        qkv_bias: Whether to add a bias to the queries, keys and values.
+        use_bias: Whether to add a bias in the feed-forward and projection layers.
+        kwargs: Keyword arguments for the [`PretrainedConfig`].
+    """
+
+    model_type: str = "aimv2"
+
+    def __init__(
+        self,
+        hidden_size: int = 1024,
+        intermediate_size: int = 2816,
+        num_hidden_layers: int = 24,
+        num_attention_heads: int = 8,
+        num_channels: int = 3,
+        image_size: int = 224,
+        patch_size: int = 14,
+        rms_norm_eps: float = 1e-5,
+        attention_dropout: float = 0.0,
+        projection_dropout: float = 0.0,
+        qkv_bias: bool = False,
+        use_bias: bool = False,
+        **kwargs: Any,
+    ):
+        super().__init__(**kwargs)
+        self.hidden_size = hidden_size
+        self.intermediate_size = intermediate_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.num_channels = num_channels
+        self.patch_size = patch_size
+        self.image_size = image_size
+        self.attention_dropout = attention_dropout
+        self.rms_norm_eps = rms_norm_eps
+
+        self.projection_dropout = projection_dropout
+        self.qkv_bias = qkv_bias
+        self.use_bias = use_bias

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:29b287f42146349615a47c0f70052749bf7e28a6cd0966f10b846a14e9daba97
+size 618413824