<commit_before># Getting started with the Keras Sequential model

The `Sequential` model is a linear stack of layers.

You can create a `Sequential` model by passing a list of layer instances to the constructor:

```python
from keras.models import Sequential

model = Sequential([
    Dense(32, input_dim=784),
    Activation('relu'),
    Dense(10),
    Activation('softmax'),
])
```

You can also simply add layers via the `.add()` method:

```python
model = Sequential()
model.add(Dense(32, input_dim=784))
model.add(Activation('relu'))<commit_msg>added required import line (#2839)<commit_after># Getting started with the Keras Sequential model

The `Sequential` model is a linear stack of layers.

You can create a `Sequential` model by passing a list of layer instances to the constructor:

```python
from keras.models import Sequential
from keras.layers import Dense, Activation

model = Sequential([
    Dense(32, input_dim=784),
    Activation('relu'),
    Dense(10),
    Activation('softmax'),
])
```

You can also simply add layers via the `.add()` method:

```python
model = Sequential()
model.add(Dense(32, input_dim=784))
model.add(Activation('relu'))
{'fraction_non_alphanumeric': 0.11769759450171821, 'fraction_numerical': 0.024054982817869417, 'mean_word_length': 5.036269430051814, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '4666546', 'n_tokens_mistral': 381, 'n_tokens_neox': 357, 'n_words': 130}