Install the Transformers, Datasets, and Evaluate libraries to run this notebook.
!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)
BertConfig { [...] "hidden_size": 768, "intermediate_size": 3072, "max_position_embeddings": 512, "num_attention_heads": 12, "num_hidden_layers": 12, [...] }
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)