BERT-based Model - 57300

import tensorflow as tf
from transformers import AutoTokenizer, TFBertModel, BertConfig

# Load the tokenizer, model and the model config
tokenizer = AutoTokenizer.from_pretrained("bert-large-uncased")
model_config = BertConfig.from_pretrained("bert-large-uncased")
model = TFBertModel.from_pretrained("bert-large-uncased", 
                                    config=model_config,)

# Prepare inputs by tokenizing the examples
inputs = tokenizer("My puppy is very cute!", return_tensors="tf")

@tf.function
def generate():
    return model(**inputs)

# Generate outputs
outputs = generate()

# Get last hidden states
last_hidden_states = outputs.last_hidden_state

# Print the shape of the last hidden states
print("Last hidden states shape:", last_hidden_states.shape)

Last hidden states shape: (1, 8, 1024)