Added a way to detach models and create them standalone

Project_Model/Libs/Transformer/Models/NanoSocratEncoder.py

@@ -0,0 +1,29 @@
+import torch
+import Project_Model.Libs.Embedder as Embedder
+from ..Classes import DeToken
+
+class NanoSocratEncoder(torch.nn.Module):
+
+    def __init__(
+        self,
+        encoder_embedder: Embedder.NanoSocratesEmbedder,
+        encoder_layers: torch.nn.Sequential,
+        detokener: DeToken
+    ) -> None:
+        super().__init__()
+
+        self.__encoder_embedder = encoder_embedder
+        self.__encoder = encoder_layers
+        self.__detokener = detokener
+
+    def forward(self,  args: tuple[torch.Tensor, torch.Tensor]):
+
+        encoder_embedder_input, src_padding = args
+
+        encoder_tensor = self.__encoder_embedder(encoder_embedder_input)
+
+        encoder_output, _ = self.__encoder((encoder_tensor, src_padding))
+
+        logits: torch.Tensor = self.__detokener(encoder_output)
+
+        return logits