grok-1/pytorch/configuration_grok_1.py
2024-03-20 10:22:10 +00:00

68 lines
2.4 KiB
Python

from transformers import PretrainedConfig
# Copied from huggingface/transformers configuration_mixtral.py.
# Modified to default values provided by xai-org/grok-1 run.py.
class Grok1Config(PretrainedConfig):
model_type = "grok-1"
keys_to_ignore_at_inference = ["past_key_values"]
def __init__(
self,
vocab_size=131072,
max_position_embeddings=8192,
output_multiplier_scale=0.5773502691896257,
embedding_multiplier_scale=78.38367176906169,
hidden_size=6144,
intermediate_size=32768,
num_hidden_layers=64,
num_attention_heads=48,
attn_output_multiplier=0.08838834764831845,
num_key_value_heads=8,
hidden_act="gelu",
initializer_range=0.02,
rms_norm_eps=1e-5,
use_cache=True,
pad_token_id=0,
bos_token_id=2,
eos_token_id=2,
tie_word_embeddings=False,
rope_theta=int(1e4),
attention_dropout=0.0,
num_experts_per_tok=2,
num_local_experts=8,
output_router_logits=False,
**kwargs,
):
self.vocab_size = vocab_size
self.max_position_embeddings = max_position_embeddings
self.output_multiplier_scale = output_multiplier_scale,
self.embedding_multiplier_scale = embedding_multiplier_scale
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.attn_output_multiplier = attn_output_multiplier
# For backward compatibility.
if num_key_value_heads is None:
num_key_value_heads = num_attention_heads
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.attention_dropout = attention_dropout
self.num_experts_per_tok = num_experts_per_tok
self.num_local_experts = num_local_experts
self.output_router_logits = output_router_logits
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,
)