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| """openPanguUltraMoE 718B model configuration""" |
|
|
| from transformers.configuration_utils import PretrainedConfig |
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|
| class PanguUltraMoEConfig(PretrainedConfig): |
|
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| model_type = "pangu_ultra_moe" |
| keys_to_ignore_at_inference = ["past_key_values"] |
|
|
| def __init__( |
| self, |
| vocab_size=153600, |
| hidden_size=7680, |
| intermediate_size=18432, |
| moe_intermediate_size=2048, |
| num_hidden_layers=61, |
| num_mtp_layers=1, |
| num_attention_heads=128, |
| num_key_value_heads=128, |
| num_shared_experts=1, |
| num_routed_experts=256, |
| routed_scaling_factor=2.5, |
| attention_kv_lora_dim=512, |
| attention_q_lora_dim=1536, |
| attention_qk_rope_dim=64, |
| attention_v_dim=128, |
| attention_qk_dim=128, |
| num_experts_per_tok=8, |
| num_dense_layers=3, |
| norm_topk_prob=True, |
| hidden_act="silu", |
| max_position_embeddings=131072, |
| initializer_range=0.02, |
| rms_norm_eps=1e-5, |
| use_cache=True, |
| pad_token_id=None, |
| bos_token_id=0, |
| eos_token_id=1, |
| tie_word_embeddings=False, |
| rope_theta=25600000, |
| attention_dropout=0.0, |
| **kwargs, |
| ): |
| self.vocab_size = vocab_size |
| self.max_position_embeddings = max_position_embeddings |
| self.hidden_size = hidden_size |
| self.num_hidden_layers = num_hidden_layers |
| self.num_attention_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.num_dense_layers = num_dense_layers |
| self.intermediate_size = intermediate_size |
| self.moe_intermediate_size = moe_intermediate_size |
| self.num_shared_experts = num_shared_experts |
| self.num_routed_experts = num_routed_experts |
| self.routed_scaling_factor = routed_scaling_factor |
| self.num_experts_per_tok = num_experts_per_tok |
| self.norm_topk_prob = norm_topk_prob |
| self.attention_kv_lora_dim = attention_kv_lora_dim |
| self.attention_q_lora_dim = attention_q_lora_dim |
| self.attention_qk_rope_dim = attention_qk_rope_dim |
| self.attention_v_dim = attention_v_dim |
| self.attention_qk_dim = attention_qk_dim |
| self.attention_dropout = attention_dropout |
| self.num_mtp_layers = num_mtp_layers |
|
|
| 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, |
| ) |
|
|
