maple-preview / configuration_maple.py
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"""Configuration for Maple models."""
from transformers.configuration_utils import PretrainedConfig
class MapleConfig(PretrainedConfig):
"""Configuration for the Maple mixture-of-experts causal language model."""
model_type = "maple"
def __init__(
self,
vocab_size=151936,
hidden_size=2048,
num_hidden_layers=20,
num_attention_heads=16,
num_key_value_heads=4,
hidden_act="silu",
use_bias=False,
rms_norm_eps=1e-6,
tie_word_embeddings=False,
attention_dropout=0.0,
initializer_range=0.02,
max_position_embeddings=32768,
rope_theta=10000.0,
use_cache=True,
rope_scaling=None,
partial_rotary_factor=0.5,
pad_token_id=None,
eos_token_id=None,
num_experts=256,
num_experts_per_tok=8,
moe_intermediate_size=512,
head_dim=128,
output_router_logits=False,
**kwargs,
):
self.num_hidden_layers = num_hidden_layers
self.vocab_size = vocab_size
self.hidden_size = hidden_size
self.num_attention_heads = num_attention_heads
self.num_key_value_heads = num_key_value_heads
self.hidden_act = hidden_act
self.use_bias = use_bias
self.rms_norm_eps = rms_norm_eps
self.attention_dropout = attention_dropout
self.initializer_range = initializer_range
self.max_position_embeddings = max_position_embeddings
self.rope_theta = rope_theta
self.use_cache = use_cache
self.head_dim = head_dim or self.hidden_size // self.num_attention_heads
self.rope_scaling = rope_scaling
self.partial_rotary_factor = partial_rotary_factor
self.num_experts = num_experts
self.num_experts_per_tok = num_experts_per_tok
self.moe_intermediate_size = moe_intermediate_size
self.output_router_logits = output_router_logits
super().__init__(
pad_token_id=pad_token_id,
eos_token_id=eos_token_id,
tie_word_embeddings=tie_word_embeddings,
**kwargs,
)