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GitHub Repository: huggingface/notebooks
 Path: blob/main/course/en/chapter2/section3_tf.ipynb
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Models (TensorFlow)

Install the Transformers, Datasets, and Evaluate libraries to run this notebook.

!pip install datasets evaluate transformers[sentencepiece]

from transformers import BertConfig, TFBertModel

# Building the config
config = BertConfig()

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

print(config)
BertConfig { [...] "hidden_size": 768, "intermediate_size": 3072, "max_position_embeddings": 512, "num_attention_heads": 12, "num_hidden_layers": 12, [...] }
from transformers import BertConfig, TFBertModel

config = BertConfig()
model = TFBertModel(config)

# Model is randomly initialized!

from transformers import TFBertModel

model = TFBertModel.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 tensorflow as tf

model_inputs = tf.constant(encoded_sequences)

output = model(model_inputs)