--- a
+++ b/mlp/mlp_model.py
@@ -0,0 +1,20 @@
+#!/usr/bin/env python
+
+import torch
+from torch import nn
+
+class MLPModel(nn.Module):
+  def __init__(self, vocab_sz, hidden_dim, dropout_p):
+    super(MLPModel, self).__init__()
+    
+    self.fc1 = nn.Linear(in_features=vocab_sz, out_features=hidden_dim)
+    self.relu = nn.ReLU()
+    self.dropout = nn.Dropout(dropout_p)
+    self.fc2 = nn.Linear(in_features=hidden_dim, out_features=1)
+
+  def forward(self, x_in):
+    x_out = self.fc1(x_in)
+    x_out = self.dropout(self.relu(x_out))
+    x_out = self.fc2(x_out)
+    
+    return x_out.squeeze(1)