cogcap / configuration_cogvlm.py
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from typing import Literal
from transformers import PretrainedConfig
class CogVLMConfig(PretrainedConfig):
_auto_class = "AutoConfig"
def __init__(
self,
vocab_size=128256,
hidden_size=4096,
intermediate_size=14336,
num_hidden_layers=32,
num_attention_heads=32,
num_multi_query_heads=8,
hidden_act='silu',
max_position_embeddings=8192,
initializer_range=0.02,
rms_norm_eps=1e-05,
template_version: Literal["base", "chat"] = "chat",
bos_token_id=128000,
eos_token_id=128001,
tie_word_embeddings=False,
use_cache=True,
**kwargs,
):
self.hidden_size = hidden_size
self.intermediate_size = intermediate_size
self.num_attention_heads = num_attention_heads
self.num_multi_query_heads = num_multi_query_heads
self.max_position_embeddings = max_position_embeddings
self.rms_norm_eps = rms_norm_eps
self.initializer_range = initializer_range
self.vocab_size = vocab_size
self.num_hidden_layers = num_hidden_layers
self.hidden_act = hidden_act
self.template_version = template_version
self.use_cache = use_cache
super().__init__(
bos_token_id=bos_token_id,
eos_token_id=eos_token_id,
tie_word_embeddings=tie_word_embeddings,
**kwargs,
)