!pip install datasets evaluate transformers[sentencepiece]

from transformers import BertConfig, BertModel

# Building the config
config = BertConfig()

# Building the model from the config
model = BertModel(config)

print(config)

from transformers import BertConfig, BertModel

config = BertConfig()
model = BertModel(config)

# Model is randomly initialized!

from transformers import BertModel

model = BertModel.from_pretrained("bert-base-cased")

model.save_pretrained("directory_on_my_computer")

sequences = ["Hello!", "Cool.", "Nice!"]

encoded_sequences = [
    [101, 7592, 999, 102],
    [101, 4658, 1012, 102],
    [101, 3835, 999, 102],
]

import torch

model_inputs = torch.tensor(encoded_sequences)

output = model(model_inputs)