section3_pt.ipynb

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مدل‌ها (PyTorch)

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)