File size: 1,402 Bytes
ed00d52 |
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 47 48 |
from transformers import PretrainedConfig
class LIMEConfig(PretrainedConfig):
model_type = "lime"
def __init__(
self,
vocab_size=50000,
d_model=1536,
num_encoder_layers=0,
num_decoder_layers=32,
num_heads=24,
dff=6144,
dropout_rate=0.0,
max_position_embeddings=512,
pad_token_id=0,
eos_token_id=1,
use_encoder=False,
use_flash=True,
multiple_of=256,
**kwargs
):
super().__init__(
pad_token_id=pad_token_id,
eos_token_id=eos_token_id,
**kwargs
)
self.vocab_size = vocab_size
self.d_model = d_model
self.num_encoder_layers = num_encoder_layers
self.num_decoder_layers = num_decoder_layers
self.num_heads = num_heads
self.dff = dff
self.dropout_rate = dropout_rate
self.max_position_embeddings = max_position_embeddings
self.pad_token_id = pad_token_id
self.eos_token_id = eos_token_id
self.use_encoder = use_encoder
self.use_flash = use_flash
self.multiple_of = multiple_of
# For Transformers library.
self.is_decoder = True
self.is_encoder_decoder = False
self.tie_word_embeddings = True
self.use_cache = False |