added model file

model.py

@@ -0,0 +1,38 @@
+import torch
+import torch.nn as nn
+from transformers import PreTrainedModel
+from transformers import AutoConfig, AutoModel, PretrainedConfig
+
+class SimpleLinearConfig(PretrainedConfig):
+    model_type = "simple-linear-model"
+
+    def __init__(self, input_dim=768, output_dim=512, **kwargs):
+        super().__init__(**kwargs)
+        self.input_dim = input_dim
+        self.output_dim = output_dim
+
+class SimpleLinearPreTrainedModel(PreTrainedModel):
+    config_class = SimpleLinearConfig
+
+    def __init__(self, config: SimpleLinearConfig):
+        super().__init__(config)
+        self.linear = nn.Linear(config.input_dim, config.output_dim)
+        self.post_init()  # This calls init_weights internally
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        return self.linear(x)
+
+    def init_weights(self):
+        # Standard weight init
+        for name, param in self.named_parameters():
+            if param.requires_grad:
+                if "weight" in name:
+                    nn.init.xavier_uniform_(param)
+                elif "bias" in name:
+                    nn.init.zeros_(param)
+
+# Register our config class with AutoConfig
+AutoConfig.register("simple-linear-model", SimpleLinearConfig)
+
+# Register our model class with AutoModel
+AutoModel.register(SimpleLinearConfig, SimpleLinearPreTrainedModel)