#@title
from IPython.display import HTML

HTML('<iframe width="560" height="315" src="https://www.youtube.com/embed/d3JVgghSOew?rel=0&amp;controls=0&amp;showinfo=0" frameborder="0" allowfullscreen></iframe>')

! pip install datasets transformers[sentencepiece]

from transformers import TFAutoModel

bert_model = TFAutoModel.from_pretrained("bert-base-cased")
print(type(bert_model))

gpt_model = TFAutoModel.from_pretrained("gpt2")
print(type(gpt_model))

bart_model = TFAutoModel.from_pretrained("facebook/bart-base")
print(type(bart_model))

from transformers import AutoConfig

bert_config = AutoConfig.from_pretrained("bert-base-cased")
print(type(bert_config))

gpt_config = AutoConfig.from_pretrained("gpt2")
print(type(gpt_config))

bart_config = AutoConfig.from_pretrained("facebook/bart-base")
print(type(bart_config))

from transformers import BertConfig

bert_config = BertConfig.from_pretrained("bert-base-cased")
print(type(bert_config))

from transformers import GPT2Config

gpt_config = GPT2Config.from_pretrained("gpt2")
print(type(gpt_config))

from transformers import BartConfig

bart_config = BartConfig.from_pretrained("facebook/bart-base")
print(type(bart_config))

from transformers import BertConfig

bert_config = BertConfig.from_pretrained("bert-base-cased")
print(bert_config)

from transformers import BertConfig, TFBertModel

bert_config = BertConfig.from_pretrained("bert-base-cased")
bert_model = TFBertModel(bert_config)

from transformers import BertConfig, TFBertModel

bert_config = BertConfig.from_pretrained("bert-base-cased")
bert_model = TFBertModel(bert_config)

# Training code

bert_model.save_pretrained("my_bert_model")