Tensorflow not working in Jupyter Notebook (Anaconda)

I did this in Linux Mint, a Ubuntu variant, and I did do pip install tensorflow and all of that, granted when I try pip3 install tensorflow, I get a wall of red text.

Relevant code is:

import tensorflow as tf

from tensorflow import keras

from tensorflow.keras import layers

#Defining the model using default linear activation function

​

model=keras.Sequential()

model.add(layers.Dense(14))

model.add(layers.Dense(4))

model.add(layers.Dense(1))

2022-02-27 11:34:48.204164: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set 2022-02-27 11:34:48.204436: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library ‘libcuda.so.1’; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory 2022-02-27 11:34:48.204446: W tensorflow/stream_executor/cuda/cuda_driver.cc:326] failed call to cuInit: UNKNOWN ERROR (303) 2022-02-27 11:34:48.204464: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (term-IdeaPad-Flex): /proc/driver/nvidia/version does not exist 2022-02-27 11:34:48.204624: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: SSE4.1 SSE4.2 AVX AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2022-02-27 11:34:48.204886: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set

I have an all AMD laptop, but I don’t see how you need NVIDIA when I see people using it in virtual machines. If you know of a way for me to fix this, or do something where I can upload to a different site, and have that work, let me know.