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