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