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+ {
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+ "model_type": "bert",
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+ "alibi_starting_size": 512,
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "classifier_dropout": null,
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+ "dtype": "float32",
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "transformers_version": "4.57.6",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 4096
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+ }
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+ # Copyright 2022 MosaicML Examples authors
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+ # SPDX-License-Identifier: Apache-2.0
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+
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+ from transformers.configuration_utils import PretrainedConfig
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+
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+
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+ class BertConfig(PretrainedConfig):
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+
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+ def __init__(
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+ self,
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+ alibi_starting_size: int = 512,
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+ attention_probs_dropout_prob: float = 0.0,
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+ **kwargs,
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+ ):
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+ """Configuration class for MosaicBert.
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+
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+ Args:
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+ alibi_starting_size (int): Use `alibi_starting_size` to determine how large of an alibi tensor to
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+ create when initializing the model. You should be able to ignore this parameter in most cases.
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+ Defaults to 512.
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+ attention_probs_dropout_prob (float): By default, turn off attention dropout in Mosaic BERT
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+ (otherwise, Flash Attention will be off by default). Defaults to 0.0.
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+ """
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+ super().__init__(
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+ attention_probs_dropout_prob=attention_probs_dropout_prob, **kwargs)
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+ self.alibi_starting_size = alibi_starting_size