| import tensorflow as tf | |
| from tensorflow import keras | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| from huggingface_hub import login | |
| (x_train,y_train),(x_test,y_test) = tf.keras.datasets.mnist.load_data() | |
| x_train,x_test = x_train/255.0,x_test/255.0 | |
| import tensorflow as tf | |
| from tensorflow import keras | |
| model = keras.models.Sequential([ | |
| keras.layers.Flatten(input_shape=(28,28)), | |
| keras.layers.Dense(128,activation='relu'), | |
| keras.layers.Dense(10,activation='softmax') | |
| ]) | |
| model.compile(optimizer='adam',loss='sparse_categorical_crossentropy',metrics=['accuracy']) | |
| model.fit(x_train,y_train,epochs=5) | |
| model.save("mnist_model.keras") | |
| login() |