Is possible test Tensorflow temporaly without Nvidia?

I am beginner in Tensorflow:
I write
import tensorflow as tf
mnist = tf.keras.datasets.mnist

(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
model = tf.keras.models.Sequential([
tf.keras.layers.Flatten(input_shape=(28, 28)),
tf.keras.layers.Dense(128, activation=‘relu’),
I have errors:
2020-07-20 18:19:12.267166: W tensorflow/stream_executor/platform/default/] Could not load dynamic library ‘’; dlerror: cannot open shared object file: No such file or directory
2020-07-20 18:19:12.267184: E tensorflow/stream_executor/cuda/] failed call to cuInit: UNKNOWN ERROR (303)
I have Ideapad and buildin graphics Card
$ inxi -G
Device-1: Intel UHD Graphics 620 driver: i915 v: kernel
Display: x11 server: X.Org 1.20.8 driver: modesetting unloaded: fbdev,vesa
resolution: 1366x768~60Hz
OpenGL: renderer: Mesa Intel UHD Graphics 620 (KBL GT2) v: 4.6 Mesa 20.0.4
I know, it will be slow, but if is possible configure Tensorflow to these card? I have Mint 20.

Tensorflwo can be run on CPU and GPU. There is separate pip package, tensorflow and tensorflow-gpu. So you can install tensorflow and run the code on CPU.

Since the last few versions the CPU and GPU editions of tensorflow have been combined as tensorflow. So there is not more tensorflow-gpu package anymore.

There is an example how to do this in the tensorflow documentation: