File size: 1,628 Bytes
3b2d368 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | from transformers import PretrainedConfig
class TransformerConfig(PretrainedConfig):
model_type = "transformer"
def __init__(
self,
# === Model Architecture ===
vocab_size=50257,
hidden_size=1024,
embedding_size=None, # if None, defaults to hidden_size
num_hidden_layers=24,
num_attention_heads=16,
intermediate_size=4096,
max_position_embeddings=1024,
max_seq_len=1024,
# === Misc ===
initializer_range=0.02,
tie_word_embeddings=True,
use_cache=False,
use_causal_attention=True,
bos_token_id=50256,
eos_token_id=50256,
pad_token_id=50256,
truncate_activation_size=False,
**kwargs,
):
super().__init__(
bos_token_id=bos_token_id,
eos_token_id=eos_token_id,
pad_token_id=pad_token_id,
tie_word_embeddings=tie_word_embeddings,
**kwargs,
)
self.vocab_size = vocab_size
self.hidden_size = hidden_size
self.embedding_size = embedding_size if embedding_size is not None else hidden_size
self.num_hidden_layers = num_hidden_layers
self.num_attention_heads = num_attention_heads
self.intermediate_size = intermediate_size
self.initializer_range = initializer_range
self.max_position_embeddings = max_position_embeddings
self.use_cache = use_cache
self.use_causal_attention = use_causal_attention
self.truncate_activation_size = truncate_activation_size
self.max_seq_len = max_seq_len |