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configuration_pawan_embd.py

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+from transformers import PretrainedConfig
+from typing import List
+
+class PawanEmbdConfig(PretrainedConfig):
+    """
+    Configuration class for PawanEmbdModel
+
+    This is the configuration class to store the configuration of a PawanEmbdModel.
+    It is used to instantiate a PawanEmbd model according to the specified arguments.
+
+    Args:
+        vocab_size (int): Vocabulary size of the model. Default: 30522
+        hidden_size (int): Dimensionality of the encoder layers. Default: 256
+        num_layers (int): Number of hidden layers in the Transformer encoder. Default: 4
+        num_heads (int): Number of attention heads. Default: 4
+        intermediate_size (int): Dimensionality of the "intermediate" layer. Default: 1024
+        output_size (int): Dimensionality of the output embeddings. Default: 768
+        max_position_embeddings (int): Maximum sequence length. Default: 512
+        dropout (float): Dropout probability. Default: 0.1
+    """
+
+    model_type = "pawan_embd"  
+
+    def __init__(
+        self,
+        vocab_size: int = 250002,
+        hidden_size: int = 256,
+        num_layers: int = 4,
+        num_heads: int = 4,
+        intermediate_size: int = 1024,
+        output_size: int = 768,
+        max_position_embeddings: int = 512,
+        dropout: float = 0.1,
+        pad_token_id: int = 1,
+        bos_token_id: int = 0,
+        eos_token_id: int = 2,
+        **kwargs
+    ):
+        super().__init__(
+            pad_token_id=pad_token_id,
+            bos_token_id=bos_token_id,
+            eos_token_id=eos_token_id,
+            **kwargs
+        )
+
+        self.vocab_size = vocab_size
+        self.hidden_size = hidden_size
+        self.num_layers = num_layers
+        self.num_heads = num_heads
+        self.intermediate_size = intermediate_size
+        self.output_size = output_size
+        self.max_position_embeddings = max_position_embeddings
+        self.dropout = dropout