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""" HelpingAI model configuration"""
from transformers import PretrainedConfig
from transformers.utils import logging
logger = logging.get_logger(__name__)
class HelpingAIConfig(PretrainedConfig):
keys_to_ignore_at_inference = ["past_key_values"]
model_type = "HelpingAI"
def __init__(
self,
vocab_size=50304,
hidden_size=2560,
intermediate_size=6912,
num_hidden_layers=32,
num_attention_heads=32,
num_key_value_heads=32,
head_dim=256,
hidden_act="silu",
max_position_embeddings=4096,
initializer_range=0.02,
rms_norm_eps=1e-6,
use_cache=True,
hidden_activation=None,
rope_theta=10000,
rope_pct=0.25,
attention_bias=False,
attention_dropout=0.0,
num_experts_per_tok=2,
num_local_experts=8,
router_aux_loss_coef=0.02,
output_router_logits=False,
norm_eps=1.0e-5,
**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.hidden_act = hidden_act
self.hidden_activation = hidden_activation
self.num_key_value_heads = num_key_value_heads
self.initializer_range = initializer_range
self.rms_norm_eps = rms_norm_eps
self.use_cache = use_cache
self.rope_theta = rope_theta
self.attention_bias = attention_bias
self.attention_dropout = attention_dropout
self.num_experts_per_tok = num_experts_per_tok
self.num_local_experts = num_local_experts
self.router_aux_loss_coef = router_aux_loss_coef
self.output_router_logits = output_router_logits
self.rope_pct = rope_pct
self.norm_eps = norm_eps
super().__init__(**kwargs)
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