one.py

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()