tiny-model

Minimalist neural network implementation for resource-constrained environments

install

pip install tiny-model

usage

import tiny_model as tm

# Define a simple network
model = tm.Sequential([
    tm.Dense(784, 128, activation='relu'),
    tm.Dense(128, 10, activation='softmax')
])

# Train on your data
model.fit(x_train, y_train, epochs=10, batch_size=32)

# Predict
predictions = model.predict(x_test)

# Export for embedded deployment
model.export('model.h', format='c_array')

license

MIT