diff --git a/tinytorch/_modidx.py b/tinytorch/_modidx.py
deleted file mode 100644
index 2048c8af..00000000
--- a/tinytorch/_modidx.py
+++ /dev/null
@@ -1,109 +0,0 @@
-# ╔═══════════════════════════════════════════════════════════════════════════════╗
-# ║                        🚨 CRITICAL WARNING 🚨                                ║
-# ║                     AUTOGENERATED! DO NOT EDIT!                              ║
-# ║                                                                               ║
-# ║  This file is AUTOMATICALLY GENERATED from source modules.                   ║
-# ║  ANY CHANGES MADE HERE WILL BE LOST when modules are re-exported!            ║
-# ║                                                                               ║
-# ║  ✅ TO EDIT: modules/source/[unknown]/[unknown]_dev.py              ║
-# ║  ✅ TO EXPORT: Run 'tito module complete <module_name>'                      ║
-# ║                                                                               ║
-# ║  🛡️ STUDENT PROTECTION: This file contains optimized implementations.        ║
-# ║     Editing it directly may break module functionality and training.         ║
-# ║                                                                               ║
-# ║  🎓 LEARNING TIP: Work in modules/source/ - that's where real development    ║
-# ║     happens! The tinytorch/ directory is just the compiled output.           ║
-# ╚═══════════════════════════════════════════════════════════════════════════════╝
-# Autogenerated by nbdev
-
-d = { 'settings': { 'branch': 'main',
-                'doc_baseurl': '/TinyTorch/',
-                'doc_host': 'https://tinytorch.github.io',
-                'git_url': 'https://github.com/tinytorch/TinyTorch/',
-                'lib_path': 'tinytorch'},
-  'syms': { 'tinytorch.benchmarking.benchmark': {},
-            'tinytorch.core.activations': { 'tinytorch.core.activations.GELU': ( '02_activations/activations_dev.html#gelu',
-                                                                                 'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.GELU.backward': ( '02_activations/activations_dev.html#gelu.backward',
-                                                                                          'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.GELU.forward': ( '02_activations/activations_dev.html#gelu.forward',
-                                                                                         'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.ReLU': ( '02_activations/activations_dev.html#relu',
-                                                                                 'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.ReLU.backward': ( '02_activations/activations_dev.html#relu.backward',
-                                                                                          'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.ReLU.forward': ( '02_activations/activations_dev.html#relu.forward',
-                                                                                         'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.Sigmoid': ( '02_activations/activations_dev.html#sigmoid',
-                                                                                    'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.Sigmoid.__call__': ( '02_activations/activations_dev.html#sigmoid.__call__',
-                                                                                             'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.Sigmoid.backward': ( '02_activations/activations_dev.html#sigmoid.backward',
-                                                                                             'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.Sigmoid.forward': ( '02_activations/activations_dev.html#sigmoid.forward',
-                                                                                            'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.Softmax': ( '02_activations/activations_dev.html#softmax',
-                                                                                    'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.Softmax.backward': ( '02_activations/activations_dev.html#softmax.backward',
-                                                                                             'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.Softmax.forward': ( '02_activations/activations_dev.html#softmax.forward',
-                                                                                            'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.Tanh': ( '02_activations/activations_dev.html#tanh',
-                                                                                 'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.Tanh.backward': ( '02_activations/activations_dev.html#tanh.backward',
-                                                                                          'tinytorch/core/activations.py'),
-                                            'tinytorch.core.activations.Tanh.forward': ( '02_activations/activations_dev.html#tanh.forward',
-                                                                                         'tinytorch/core/activations.py')},
-            'tinytorch.core.layers': { 'tinytorch.core.layers.Dropout': ('03_layers/layers_dev.html#dropout', 'tinytorch/core/layers.py'),
-                                       'tinytorch.core.layers.Dropout.__init__': ( '03_layers/layers_dev.html#dropout.__init__',
-                                                                                   'tinytorch/core/layers.py'),
-                                       'tinytorch.core.layers.Dropout.__repr__': ( '03_layers/layers_dev.html#dropout.__repr__',
-                                                                                   'tinytorch/core/layers.py'),
-                                       'tinytorch.core.layers.Dropout.forward': ( '03_layers/layers_dev.html#dropout.forward',
-                                                                                  'tinytorch/core/layers.py'),
-                                       'tinytorch.core.layers.Dropout.parameters': ( '03_layers/layers_dev.html#dropout.parameters',
-                                                                                     'tinytorch/core/layers.py'),
-                                       'tinytorch.core.layers.Linear': ('03_layers/layers_dev.html#linear', 'tinytorch/core/layers.py'),
-                                       'tinytorch.core.layers.Linear.__call__': ( '03_layers/layers_dev.html#linear.__call__',
-                                                                                  'tinytorch/core/layers.py'),
-                                       'tinytorch.core.layers.Linear.__init__': ( '03_layers/layers_dev.html#linear.__init__',
-                                                                                  'tinytorch/core/layers.py'),
-                                       'tinytorch.core.layers.Linear.__repr__': ( '03_layers/layers_dev.html#linear.__repr__',
-                                                                                  'tinytorch/core/layers.py'),
-                                       'tinytorch.core.layers.Linear.forward': ( '03_layers/layers_dev.html#linear.forward',
-                                                                                 'tinytorch/core/layers.py'),
-                                       'tinytorch.core.layers.Linear.parameters': ( '03_layers/layers_dev.html#linear.parameters',
-                                                                                    'tinytorch/core/layers.py')},
-            'tinytorch.core.tensor': { 'tinytorch.core.tensor.Tensor': ('01_tensor/tensor_dev.html#tensor', 'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.__add__': ( '01_tensor/tensor_dev.html#tensor.__add__',
-                                                                                 'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.__init__': ( '01_tensor/tensor_dev.html#tensor.__init__',
-                                                                                  'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.__mul__': ( '01_tensor/tensor_dev.html#tensor.__mul__',
-                                                                                 'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.__repr__': ( '01_tensor/tensor_dev.html#tensor.__repr__',
-                                                                                  'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.__str__': ( '01_tensor/tensor_dev.html#tensor.__str__',
-                                                                                 'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.__sub__': ( '01_tensor/tensor_dev.html#tensor.__sub__',
-                                                                                 'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.__truediv__': ( '01_tensor/tensor_dev.html#tensor.__truediv__',
-                                                                                     'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.backward': ( '01_tensor/tensor_dev.html#tensor.backward',
-                                                                                  'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.matmul': ( '01_tensor/tensor_dev.html#tensor.matmul',
-                                                                                'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.max': ( '01_tensor/tensor_dev.html#tensor.max',
-                                                                             'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.mean': ( '01_tensor/tensor_dev.html#tensor.mean',
-                                                                              'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.numpy': ( '01_tensor/tensor_dev.html#tensor.numpy',
-                                                                               'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.reshape': ( '01_tensor/tensor_dev.html#tensor.reshape',
-                                                                                 'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.sum': ( '01_tensor/tensor_dev.html#tensor.sum',
-                                                                             'tinytorch/core/tensor.py'),
-                                       'tinytorch.core.tensor.Tensor.transpose': ( '01_tensor/tensor_dev.html#tensor.transpose',
-                                                                                   'tinytorch/core/tensor.py')},
-            'tinytorch.data.loader': {},
-            'tinytorch.profiling.profiler': {}}}
diff --git a/tinytorch/applications/__init__.py b/tinytorch/applications/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/tinytorch/applications/tinygpt.py b/tinytorch/applications/tinygpt.py
new file mode 100644
index 00000000..80dabc9a
--- /dev/null
+++ b/tinytorch/applications/tinygpt.py
@@ -0,0 +1,8 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/20_capstone/capstone_dev.ipynb.
+
+# %% auto 0
+__all__ = []
+
+# %% ../../modules/source/20_capstone/capstone_dev.ipynb 2
+#| default_exp applications.tinygpt
+#| export
diff --git a/tinytorch/benchmarking/benchmark.py b/tinytorch/benchmarking/benchmark.py
index 8856ac98..59888381 100644
--- a/tinytorch/benchmarking/benchmark.py
+++ b/tinytorch/benchmarking/benchmark.py
@@ -1,19 +1,5 @@
-# ╔═══════════════════════════════════════════════════════════════════════════════╗
-# ║                        🚨 CRITICAL WARNING 🚨                                ║
-# ║                     AUTOGENERATED! DO NOT EDIT!                              ║
-# ║                                                                               ║
-# ║  This file is AUTOMATICALLY GENERATED from source modules.                   ║
-# ║  ANY CHANGES MADE HERE WILL BE LOST when modules are re-exported!            ║
-# ║                                                                               ║
-# ║  ✅ TO EDIT: modules/source/XX_benchmark/benchmark_dev.py           ║
-# ║  ✅ TO EXPORT: Run 'tito module complete <module_name>'                      ║
-# ║                                                                               ║
-# ║  🛡️ STUDENT PROTECTION: This file contains optimized implementations.        ║
-# ║     Editing it directly may break module functionality and training.         ║
-# ║                                                                               ║
-# ║  🎓 LEARNING TIP: Work in modules/source/ - that's where real development    ║
-# ║     happens! The tinytorch/ directory is just the compiled output.           ║
-# ╚═══════════════════════════════════════════════════════════════════════════════╝
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/19_benchmarking/benchmarking_dev.ipynb.
+
 # %% auto 0
 __all__ = []
 
diff --git a/tinytorch/core/activations.py b/tinytorch/core/activations.py
index 7ea930a0..a61df44b 100644
--- a/tinytorch/core/activations.py
+++ b/tinytorch/core/activations.py
@@ -1,19 +1,5 @@
-# ╔═══════════════════════════════════════════════════════════════════════════════╗
-# ║                        🚨 CRITICAL WARNING 🚨                                ║
-# ║                     AUTOGENERATED! DO NOT EDIT!                              ║
-# ║                                                                               ║
-# ║  This file is AUTOMATICALLY GENERATED from source modules.                   ║
-# ║  ANY CHANGES MADE HERE WILL BE LOST when modules are re-exported!            ║
-# ║                                                                               ║
-# ║  ✅ TO EDIT: modules/source/03_activations/activations_dev.py       ║
-# ║  ✅ TO EXPORT: Run 'tito module complete <module_name>'                      ║
-# ║                                                                               ║
-# ║  🛡️ STUDENT PROTECTION: This file contains optimized implementations.        ║
-# ║     Editing it directly may break module functionality and training.         ║
-# ║                                                                               ║
-# ║  🎓 LEARNING TIP: Work in modules/source/ - that's where real development    ║
-# ║     happens! The tinytorch/ directory is just the compiled output.           ║
-# ╚═══════════════════════════════════════════════════════════════════════════════╝
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/02_activations/activations_dev.ipynb.
+
 # %% auto 0
 __all__ = ['Sigmoid', 'ReLU', 'Tanh', 'GELU', 'Softmax']
 
diff --git a/tinytorch/core/attention.py b/tinytorch/core/attention.py
new file mode 100644
index 00000000..7d6df426
--- /dev/null
+++ b/tinytorch/core/attention.py
@@ -0,0 +1,8 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/12_attention/attention_dev.ipynb.
+
+# %% auto 0
+__all__ = []
+
+# %% ../../modules/source/12_attention/attention_dev.ipynb 0
+#| default_exp core.attention
+#| export
diff --git a/tinytorch/core/autograd.py b/tinytorch/core/autograd.py
new file mode 100644
index 00000000..dcc565d8
--- /dev/null
+++ b/tinytorch/core/autograd.py
@@ -0,0 +1,12 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/05_autograd/autograd_dev.ipynb.
+
+# %% auto 0
+__all__ = []
+
+# %% ../../modules/source/05_autograd/autograd_dev.ipynb 1
+import numpy as np
+from typing import Optional, List, Tuple
+import sys
+import os
+
+from .tensor import Tensor
diff --git a/tinytorch/core/layers.py b/tinytorch/core/layers.py
index 2f117f88..7ea028c4 100644
--- a/tinytorch/core/layers.py
+++ b/tinytorch/core/layers.py
@@ -1,19 +1,5 @@
-# ╔═══════════════════════════════════════════════════════════════════════════════╗
-# ║                        🚨 CRITICAL WARNING 🚨                                ║
-# ║                     AUTOGENERATED! DO NOT EDIT!                              ║
-# ║                                                                               ║
-# ║  This file is AUTOMATICALLY GENERATED from source modules.                   ║
-# ║  ANY CHANGES MADE HERE WILL BE LOST when modules are re-exported!            ║
-# ║                                                                               ║
-# ║  ✅ TO EDIT: modules/source/04_layers/layers_dev.py                 ║
-# ║  ✅ TO EXPORT: Run 'tito module complete <module_name>'                      ║
-# ║                                                                               ║
-# ║  🛡️ STUDENT PROTECTION: This file contains optimized implementations.        ║
-# ║     Editing it directly may break module functionality and training.         ║
-# ║                                                                               ║
-# ║  🎓 LEARNING TIP: Work in modules/source/ - that's where real development    ║
-# ║     happens! The tinytorch/ directory is just the compiled output.           ║
-# ╚═══════════════════════════════════════════════════════════════════════════════╝
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/03_layers/layers_dev.ipynb.
+
 # %% auto 0
 __all__ = ['Linear', 'Dropout']
 
diff --git a/tinytorch/core/losses.py b/tinytorch/core/losses.py
new file mode 100644
index 00000000..8e72375c
--- /dev/null
+++ b/tinytorch/core/losses.py
@@ -0,0 +1,22 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/04_losses/losses_dev.ipynb.
+
+# %% auto 0
+__all__ = ['import_previous_module']
+
+# %% ../../modules/source/04_losses/losses_dev.ipynb 3
+import numpy as np
+import matplotlib.pyplot as plt
+import time
+from typing import Optional
+
+def import_previous_module(module_name: str, component_name: str):
+    import sys
+    import os
+    sys.path.append(os.path.join(os.path.dirname(__file__), '..', module_name))
+    module = __import__(f"{module_name.split('_')[1]}_dev")
+    return getattr(module, component_name)
+
+# Import from tinytorch package
+from .tensor import Tensor
+from .layers import Linear
+from .activations import ReLU
diff --git a/tinytorch/core/optimizers.py b/tinytorch/core/optimizers.py
new file mode 100644
index 00000000..1d39357d
--- /dev/null
+++ b/tinytorch/core/optimizers.py
@@ -0,0 +1,14 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/06_optimizers/optimizers_dev.ipynb.
+
+# %% auto 0
+__all__ = []
+
+# %% ../../modules/source/06_optimizers/optimizers_dev.ipynb 1
+import numpy as np
+from typing import List, Union, Optional, Dict, Any
+
+# Import Tensor from Module 01 (now with gradient support from Module 05)
+import sys
+import os
+sys.path.append(os.path.join(os.path.dirname(__file__), '..', '01_tensor'))
+from tensor_dev import Tensor
diff --git a/tinytorch/core/spatial.py b/tinytorch/core/spatial.py
new file mode 100644
index 00000000..faa47403
--- /dev/null
+++ b/tinytorch/core/spatial.py
@@ -0,0 +1,64 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/09_spatial/spatial_dev.ipynb.
+
+# %% auto 0
+__all__ = []
+
+# %% ../../modules/source/09_spatial/spatial_dev.ipynb 1
+import numpy as np
+import sys
+import os
+import time
+
+# Import dependencies from other modules
+sys.path.append(os.path.join(os.path.dirname(__file__), '..', '01_tensor'))
+from tensor_dev import Tensor
+
+sys.path.append(os.path.join(os.path.dirname(__file__), '..', '03_layers'))
+from layers_dev import Module
+
+# Note: Keeping simplified implementations for reference during development
+class _SimplifiedTensor:
+        """Simplified tensor for spatial operations development."""
+
+        def __init__(self, data, requires_grad=False):
+            self.data = np.array(data, dtype=np.float32)
+            self.shape = self.data.shape
+            self.requires_grad = requires_grad
+            self.grad = None
+
+        def __repr__(self):
+            return f"Tensor(shape={self.shape}, data=\n{self.data})"
+
+        def __add__(self, other):
+            if isinstance(other, Tensor):
+                return Tensor(self.data + other.data)
+            return Tensor(self.data + other)
+
+        def __mul__(self, other):
+            if isinstance(other, Tensor):
+                return Tensor(self.data * other.data)
+            return Tensor(self.data * other)
+
+        def sum(self):
+            return Tensor(np.sum(self.data))
+
+        def mean(self):
+            return Tensor(np.mean(self.data))
+
+    # Create a simple Module base class for inheritance
+    class Module:
+        """Simple base class for neural network modules."""
+        def __init__(self):
+            pass
+
+        def forward(self, x):
+            raise NotImplementedError("Subclasses must implement forward()")
+
+        def parameters(self):
+            """Return list of parameters for this module."""
+            params = []
+            for attr_name in dir(self):
+                attr = getattr(self, attr_name)
+                if hasattr(attr, 'data') and hasattr(attr, 'requires_grad'):
+                    params.append(attr)
+            return params
diff --git a/tinytorch/core/tensor.py b/tinytorch/core/tensor.py
index fb786066..22b11dad 100644
--- a/tinytorch/core/tensor.py
+++ b/tinytorch/core/tensor.py
@@ -1,19 +1,5 @@
-# ╔═══════════════════════════════════════════════════════════════════════════════╗
-# ║                        🚨 CRITICAL WARNING 🚨                                ║
-# ║                     AUTOGENERATED! DO NOT EDIT!                              ║
-# ║                                                                               ║
-# ║  This file is AUTOMATICALLY GENERATED from source modules.                   ║
-# ║  ANY CHANGES MADE HERE WILL BE LOST when modules are re-exported!            ║
-# ║                                                                               ║
-# ║  ✅ TO EDIT: modules/source/02_tensor/tensor_dev.py                 ║
-# ║  ✅ TO EXPORT: Run 'tito module complete <module_name>'                      ║
-# ║                                                                               ║
-# ║  🛡️ STUDENT PROTECTION: This file contains optimized implementations.        ║
-# ║     Editing it directly may break module functionality and training.         ║
-# ║                                                                               ║
-# ║  🎓 LEARNING TIP: Work in modules/source/ - that's where real development    ║
-# ║     happens! The tinytorch/ directory is just the compiled output.           ║
-# ╚═══════════════════════════════════════════════════════════════════════════════╝
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/01_tensor/tensor_dev.ipynb.
+
 # %% auto 0
 __all__ = ['Tensor']
 
diff --git a/tinytorch/core/training.py b/tinytorch/core/training.py
new file mode 100644
index 00000000..54947841
--- /dev/null
+++ b/tinytorch/core/training.py
@@ -0,0 +1,26 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/07_training/training_dev.ipynb.
+
+# %% auto 0
+__all__ = []
+
+# %% ../../modules/source/07_training/training_dev.ipynb 1
+import numpy as np
+import pickle
+import time
+from typing import Dict, List, Optional, Tuple, Any, Callable
+from pathlib import Path
+import sys
+import os
+
+# Import dependencies from other modules
+sys.path.append(os.path.join(os.path.dirname(__file__), '..', '01_tensor'))
+from tensor_dev import Tensor
+
+sys.path.append(os.path.join(os.path.dirname(__file__), '..', '03_layers'))
+from layers_dev import Linear
+
+sys.path.append(os.path.join(os.path.dirname(__file__), '..', '04_losses'))
+from losses_dev import MSELoss, CrossEntropyLoss
+
+sys.path.append(os.path.join(os.path.dirname(__file__), '..', '06_optimizers'))
+from optimizers_dev import SGD, AdamW
diff --git a/tinytorch/generation/__init__.py b/tinytorch/generation/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/tinytorch/generation/kv_cache.py b/tinytorch/generation/kv_cache.py
new file mode 100644
index 00000000..ed623a38
--- /dev/null
+++ b/tinytorch/generation/kv_cache.py
@@ -0,0 +1,57 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/14_kvcaching/kvcaching_dev.ipynb.
+
+# %% auto 0
+__all__ = ['Tensor']
+
+# %% ../../modules/source/14_kvcaching/kvcaching_dev.ipynb 1
+import numpy as np
+import time
+from typing import Tuple, Optional, Dict, List
+from dataclasses import dataclass
+
+# Import our TinyTorch components (Modules 01-13)
+### BEGIN SOLUTION
+# Note: In real implementation, these would import from previous modules
+# For now, we'll implement minimal versions to focus on caching concepts
+
+class Tensor:
+    """Minimal Tensor for KV Caching focus (from Module 01)"""
+    def __init__(self, data, requires_grad=False):
+        self.data = np.array(data)
+        self.shape = self.data.shape
+        self.requires_grad = requires_grad
+        self.grad = None
+
+    def __getitem__(self, key):
+        return Tensor(self.data[key])
+
+    def __setitem__(self, key, value):
+        if isinstance(value, Tensor):
+            self.data[key] = value.data
+        else:
+            self.data[key] = value
+
+    def size(self, dim=None):
+        if dim is None:
+            return self.shape
+        return self.shape[dim]
+
+    def view(self, *shape):
+        return Tensor(self.data.reshape(shape))
+
+    def transpose(self, dim0, dim1):
+        axes = list(range(len(self.shape)))
+        axes[dim0], axes[dim1] = axes[dim1], axes[dim0]
+        return Tensor(np.transpose(self.data, axes))
+
+    @staticmethod
+    def cat(tensors, dim=0):
+        """Concatenate tensors along dimension"""
+        arrays = [t.data for t in tensors]
+        return Tensor(np.concatenate(arrays, axis=dim))
+
+    @staticmethod
+    def zeros(*shape):
+        """Create zero tensor"""
+        return Tensor(np.zeros(shape))
+### END SOLUTION
diff --git a/tinytorch/models/__init__.py b/tinytorch/models/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/tinytorch/models/transformer.py b/tinytorch/models/transformer.py
new file mode 100644
index 00000000..6e63d29b
--- /dev/null
+++ b/tinytorch/models/transformer.py
@@ -0,0 +1,148 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/13_transformers/transformers_dev.ipynb.
+
+# %% auto 0
+__all__ = ['Tensor', 'Linear', 'MultiHeadAttention', 'Embedding', 'gelu']
+
+# %% ../../modules/source/13_transformers/transformers_dev.ipynb 1
+import numpy as np
+import math
+from typing import Optional, List
+
+# Minimal implementations for development - in practice these import from previous modules
+class Tensor:
+    """Minimal Tensor class for transformer development - imports from Module 01 in practice."""
+    def __init__(self, data, requires_grad=False):
+        self.data = np.array(data)
+        self.shape = self.data.shape
+        self.size = self.data.size
+        self.requires_grad = requires_grad
+        self.grad = None
+
+    def __add__(self, other):
+        if isinstance(other, Tensor):
+            return Tensor(self.data + other.data)
+        return Tensor(self.data + other)
+
+    def __mul__(self, other):
+        if isinstance(other, Tensor):
+            return Tensor(self.data * other.data)
+        return Tensor(self.data * other)
+
+    def matmul(self, other):
+        return Tensor(np.dot(self.data, other.data))
+
+    def sum(self, axis=None, keepdims=False):
+        return Tensor(self.data.sum(axis=axis, keepdims=keepdims))
+
+    def mean(self, axis=None, keepdims=False):
+        return Tensor(self.data.mean(axis=axis, keepdims=keepdims))
+
+    def reshape(self, *shape):
+        return Tensor(self.data.reshape(shape))
+
+    def __repr__(self):
+        return f"Tensor(data={self.data}, shape={self.shape})"
+
+class Linear:
+    """Minimal Linear layer - imports from Module 03 in practice."""
+    def __init__(self, in_features, out_features, bias=True):
+        # Xavier/Glorot initialization
+        std = math.sqrt(2.0 / (in_features + out_features))
+        self.weight = Tensor(np.random.normal(0, std, (in_features, out_features)))
+        self.bias = Tensor(np.zeros(out_features)) if bias else None
+
+    def forward(self, x):
+        output = x.matmul(self.weight)
+        if self.bias is not None:
+            output = output + self.bias
+        return output
+
+    def parameters(self):
+        params = [self.weight]
+        if self.bias is not None:
+            params.append(self.bias)
+        return params
+
+class MultiHeadAttention:
+    """Minimal MultiHeadAttention - imports from Module 12 in practice."""
+    def __init__(self, embed_dim, num_heads):
+        assert embed_dim % num_heads == 0
+        self.embed_dim = embed_dim
+        self.num_heads = num_heads
+        self.head_dim = embed_dim // num_heads
+
+        self.q_proj = Linear(embed_dim, embed_dim)
+        self.k_proj = Linear(embed_dim, embed_dim)
+        self.v_proj = Linear(embed_dim, embed_dim)
+        self.out_proj = Linear(embed_dim, embed_dim)
+
+    def forward(self, x, mask=None):
+        batch_size, seq_len, embed_dim = x.shape
+
+        # Linear projections
+        Q = self.q_proj.forward(x)
+        K = self.k_proj.forward(x)
+        V = self.v_proj.forward(x)
+
+        # Reshape for multi-head attention
+        Q = Q.reshape(batch_size, seq_len, self.num_heads, self.head_dim)
+        K = K.reshape(batch_size, seq_len, self.num_heads, self.head_dim)
+        V = V.reshape(batch_size, seq_len, self.num_heads, self.head_dim)
+
+        # Transpose to (batch_size, num_heads, seq_len, head_dim)
+        Q = Tensor(np.transpose(Q.data, (0, 2, 1, 3)))
+        K = Tensor(np.transpose(K.data, (0, 2, 1, 3)))
+        V = Tensor(np.transpose(V.data, (0, 2, 1, 3)))
+
+        # Scaled dot-product attention
+        scores = Tensor(np.matmul(Q.data, np.transpose(K.data, (0, 1, 3, 2))))
+        scores = scores * (1.0 / math.sqrt(self.head_dim))
+
+        # Apply causal mask for autoregressive generation
+        if mask is not None:
+            scores = Tensor(scores.data + mask.data)
+
+        # Softmax
+        attention_weights = self._softmax(scores)
+
+        # Apply attention to values
+        out = Tensor(np.matmul(attention_weights.data, V.data))
+
+        # Transpose back and reshape
+        out = Tensor(np.transpose(out.data, (0, 2, 1, 3)))
+        out = out.reshape(batch_size, seq_len, embed_dim)
+
+        # Final linear projection
+        return self.out_proj.forward(out)
+
+    def _softmax(self, x):
+        """Numerically stable softmax."""
+        exp_x = Tensor(np.exp(x.data - np.max(x.data, axis=-1, keepdims=True)))
+        return Tensor(exp_x.data / np.sum(exp_x.data, axis=-1, keepdims=True))
+
+    def parameters(self):
+        params = []
+        params.extend(self.q_proj.parameters())
+        params.extend(self.k_proj.parameters())
+        params.extend(self.v_proj.parameters())
+        params.extend(self.out_proj.parameters())
+        return params
+
+class Embedding:
+    """Minimal Embedding layer - imports from Module 11 in practice."""
+    def __init__(self, vocab_size, embed_dim):
+        self.vocab_size = vocab_size
+        self.embed_dim = embed_dim
+        # Initialize with small random values
+        self.weight = Tensor(np.random.normal(0, 0.02, (vocab_size, embed_dim)))
+
+    def forward(self, indices):
+        # Simple embedding lookup
+        return Tensor(self.weight.data[indices.data])
+
+    def parameters(self):
+        return [self.weight]
+
+def gelu(x):
+    """GELU activation function."""
+    return Tensor(0.5 * x.data * (1 + np.tanh(np.sqrt(2 / np.pi) * (x.data + 0.044715 * x.data**3))))
diff --git a/tinytorch/optimization/__init__.py b/tinytorch/optimization/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/tinytorch/optimization/acceleration.py b/tinytorch/optimization/acceleration.py
new file mode 100644
index 00000000..d0ca1d13
--- /dev/null
+++ b/tinytorch/optimization/acceleration.py
@@ -0,0 +1,8 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/16_acceleration/acceleration_dev.ipynb.
+
+# %% auto 0
+__all__ = []
+
+# %% ../../modules/source/16_acceleration/acceleration_dev.ipynb 0
+#| default_exp optimization.acceleration
+#| export
diff --git a/tinytorch/optimization/compression.py b/tinytorch/optimization/compression.py
new file mode 100644
index 00000000..01ef28ae
--- /dev/null
+++ b/tinytorch/optimization/compression.py
@@ -0,0 +1,85 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/18_compression/compression_dev.ipynb.
+
+# %% auto 0
+__all__ = ['Tensor', 'Linear', 'Sequential']
+
+# %% ../../modules/source/18_compression/compression_dev.ipynb 1
+import numpy as np
+import copy
+from typing import List, Dict, Any, Tuple, Optional
+import time
+
+# Import from previous modules
+# Note: In the full package, these would be imports like:
+# from tinytorch.core.tensor import Tensor
+# from tinytorch.core.layers import Linear
+# For development, we'll create minimal implementations
+
+class Tensor:
+    """Minimal Tensor class for compression development - imports from Module 01 in practice."""
+    def __init__(self, data, requires_grad=False):
+        self.data = np.array(data)
+        self.shape = self.data.shape
+        self.size = self.data.size
+        self.requires_grad = requires_grad
+        self.grad = None
+
+    def __add__(self, other):
+        if isinstance(other, Tensor):
+            return Tensor(self.data + other.data)
+        return Tensor(self.data + other)
+
+    def __mul__(self, other):
+        if isinstance(other, Tensor):
+            return Tensor(self.data * other.data)
+        return Tensor(self.data * other)
+
+    def matmul(self, other):
+        return Tensor(np.dot(self.data, other.data))
+
+    def abs(self):
+        return Tensor(np.abs(self.data))
+
+    def sum(self, axis=None):
+        return Tensor(self.data.sum(axis=axis))
+
+    def __repr__(self):
+        return f"Tensor(shape={self.shape})"
+
+class Linear:
+    """Minimal Linear layer for compression development - imports from Module 03 in practice."""
+    def __init__(self, in_features, out_features, bias=True):
+        self.in_features = in_features
+        self.out_features = out_features
+        # Initialize with He initialization
+        self.weight = Tensor(np.random.randn(in_features, out_features) * np.sqrt(2.0 / in_features))
+        self.bias = Tensor(np.zeros(out_features)) if bias else None
+
+    def forward(self, x):
+        output = x.matmul(self.weight)
+        if self.bias is not None:
+            output = output + self.bias
+        return output
+
+    def parameters(self):
+        params = [self.weight]
+        if self.bias is not None:
+            params.append(self.bias)
+        return params
+
+class Sequential:
+    """Minimal Sequential container for model compression."""
+    def __init__(self, *layers):
+        self.layers = list(layers)
+
+    def forward(self, x):
+        for layer in self.layers:
+            x = layer.forward(x)
+        return x
+
+    def parameters(self):
+        params = []
+        for layer in self.layers:
+            if hasattr(layer, 'parameters'):
+                params.extend(layer.parameters())
+        return params
diff --git a/tinytorch/optimization/quantization.py b/tinytorch/optimization/quantization.py
new file mode 100644
index 00000000..f5bc7cfd
--- /dev/null
+++ b/tinytorch/optimization/quantization.py
@@ -0,0 +1,8 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/17_quantization/quantization_dev.ipynb.
+
+# %% auto 0
+__all__ = []
+
+# %% ../../modules/source/17_quantization/quantization_dev.ipynb 0
+#| default_exp optimization.quantization
+#| export
diff --git a/tinytorch/profiling/profiler.py b/tinytorch/profiling/profiler.py
index f87c5764..82aca521 100644
--- a/tinytorch/profiling/profiler.py
+++ b/tinytorch/profiling/profiler.py
@@ -1,19 +1,5 @@
-# ╔═══════════════════════════════════════════════════════════════════════════════╗
-# ║                        🚨 CRITICAL WARNING 🚨                                ║
-# ║                     AUTOGENERATED! DO NOT EDIT!                              ║
-# ║                                                                               ║
-# ║  This file is AUTOMATICALLY GENERATED from source modules.                   ║
-# ║  ANY CHANGES MADE HERE WILL BE LOST when modules are re-exported!            ║
-# ║                                                                               ║
-# ║  ✅ TO EDIT: modules/source/XX_profiler/profiler_dev.py             ║
-# ║  ✅ TO EXPORT: Run 'tito module complete <module_name>'                      ║
-# ║                                                                               ║
-# ║  🛡️ STUDENT PROTECTION: This file contains optimized implementations.        ║
-# ║     Editing it directly may break module functionality and training.         ║
-# ║                                                                               ║
-# ║  🎓 LEARNING TIP: Work in modules/source/ - that's where real development    ║
-# ║     happens! The tinytorch/ directory is just the compiled output.           ║
-# ╚═══════════════════════════════════════════════════════════════════════════════╝
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/15_profiling/profiling_dev.ipynb.
+
 # %% auto 0
 __all__ = []
 
diff --git a/tinytorch/text/__init__.py b/tinytorch/text/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/tinytorch/text/tokenization.py b/tinytorch/text/tokenization.py
new file mode 100644
index 00000000..10a40e63
--- /dev/null
+++ b/tinytorch/text/tokenization.py
@@ -0,0 +1,8 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../../modules/source/10_tokenization/tokenization_dev.ipynb.
+
+# %% auto 0
+__all__ = []
+
+# %% ../../modules/source/10_tokenization/tokenization_dev.ipynb 0
+#| default_exp text.tokenization
+#| export