title: load bert file with configuration file and tokenizer
body: <p>I want to save my trained bert model on my data to use it in visualization method
  I use this code for save my model</p>
  <pre><code>model = TFAutoModelForSequenceClassification.from_pretrained(&quot;bert-base-uncased&quot;, num_labels=6)
  tokenizer =BertTokenizer.from_pretrained(&quot;bert-base-uncased&quot;)
  model_save_path= '/content/drive/My Drive/Colab Notebooks/bert_visualization2.h5py'
  
  
  my_callbacks = [
       
      tf.keras.callbacks.ModelCheckpoint(filepath=model_save_path,save_weights_only=False,monitor='val_0accuracy',mode='max'),keras.callbacks.TensorBoard(log_dir=log_dir)]
  model.compile(loss=loss,optimizer=optimizer,metrics=[metric])
  
  history=model.fit([train_inp,train_mask],train_label,batch_size=64,epochs=1
                       ,validation_data=([val_inp,val_mask],val_label),callbacks=my_callbacks, class_weight=class_weights)
  </code></pre>
  <p>i want to use file saved by callbacks to visualize how does bert work? and which are words help it most in classification process?
  I use code in this link
  &lt; <a href="https://github.com/cdpierse/transformers-interpret/blob/master/notebooks/multiclass_classification_example.ipynb" rel="nofollow noreferrer">https://github.com/cdpierse/transformers-interpret/blob/master/notebooks/multiclass_classification_example.ipynb</a> &gt;</p>