Added a way to detach models and create them standalone

Project_Model/Libs/Transformer/Models/NanoSocraDecoder.py

@@ -0,0 +1,32 @@
+import torch
+import Project_Model.Libs.Embedder as Embedder
+from ..Classes import DeToken
+
+class NanoSocraDecoder(torch.nn.Module):
+
+    def __init__(
+        self,
+        decoder_embedder: Embedder.NanoSocratesEmbedder,
+        decoder_layers: torch.nn.Sequential,
+        detokener: DeToken
+    ) -> None:
+        super().__init__()
+
+
+        self.__decoder_embedder = decoder_embedder
+        self.__decoder = decoder_layers
+        self.__detokener = detokener
+
+    def forward(self, args: tuple[torch.Tensor, torch.Tensor]):
+
+        decoder_embedder_input, tgt_padding = args
+
+        decoder_tensor = self.__decoder_embedder(decoder_embedder_input)
+
+        decoder_output, _, _, _, _, _ = self.__decoder(
+            (decoder_tensor, decoder_tensor, decoder_tensor, tgt_padding, tgt_padding, False)
+        )
+
+        logits: torch.Tensor = self.__detokener(decoder_output)
+
+        return logits