Continue-1-OSS / configuration_continue_oss.py
SVECTOR-OFFICIAL's picture
Upload 11 files
e0b4985 verified
"""Continue-1-OSS model configuration"""
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import logging
logger = logging.get_logger(__name__)
class Continue1Config(PretrainedConfig):
model_type = "continue_oss"
keys_to_ignore_at_inference = ["past_key_values"]
def __init__(
self,
vocab_size=128256,
hidden_size=3072,
intermediate_size=8192,
num_hidden_layers=28,
num_attention_heads=24,
num_key_value_heads=8,
head_dim=128,
hidden_act="silu",
max_position_embeddings=131072,
initializer_range=0.02,
rms_norm_eps=1e-5,
use_cache=True,
pad_token_id=None,
bos_token_id=128000,
eos_token_id=128009,
tie_word_embeddings=True,
rope_theta=500000.0,
rope_scaling=None,
attention_bias=False,
attention_dropout=0.0,
mlp_bias=False,
**kwargs,
):
self.vocab_size = vocab_size
self.max_position_embeddings = max_position_embeddings
self.hidden_size = hidden_size
self.intermediate_size = intermediate_size
self.num_hidden_layers = num_hidden_layers
self.num_attention_heads = num_attention_heads
self.head_dim = head_dim
self.num_key_value_heads = num_key_value_heads
self.hidden_act = hidden_act
self.initializer_range = initializer_range
self.rms_norm_eps = rms_norm_eps
self.use_cache = use_cache
self.rope_theta = rope_theta
self.rope_scaling = rope_scaling
self.attention_bias = attention_bias
self.attention_dropout = attention_dropout
self.mlp_bias = mlp_bias
super().__init__(
pad_token_id=pad_token_id,
bos_token_id=bos_token_id,
eos_token_id=eos_token_id,
tie_word_embeddings=tie_word_embeddings,
**kwargs,
)