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init model

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  1. config.json +44 -0
  2. configuration_bailing_moe.py +78 -0
  3. md5sums.txt +60 -0
  4. model-00001-of-00052.safetensors +3 -0
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config.json ADDED
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+ {
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+ "architectures": [
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+ "BailingMoeForCausalLM"
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+ ],
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+ "attention_dropout": 0.0,
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+ "auto_map": {
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+ "AutoConfig": "configuration_bailing_moe.BailingMoeConfig",
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+ "AutoModel": "modeling_bailing_moe.BailingMoeModel",
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+ "AutoModelForCausalLM": "modeling_bailing_moe.BailingMoeForCausalLM"
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+ },
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+ "eos_token_id": 126081,
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+ "pad_token_id": 126081,
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+ "first_k_dense_replace": 0,
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+ "hidden_act": "silu",
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+ "hidden_size": 5376,
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+ "initializer_range": 0.006,
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+ "intermediate_size": 12288,
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+ "max_position_embeddings": 16384,
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+ "model_type": "bailing_moe",
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+ "moe_intermediate_size": 3072,
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+ "num_experts": 64,
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+ "num_shared_experts": 1,
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+ "norm_topk_prob": true,
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+ "num_attention_heads": 42,
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+ "num_experts_per_tok": 4,
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+ "num_hidden_layers": 88,
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+ "num_key_value_heads": 6,
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+ "pretraining_tp": 1,
29
+ "rms_norm_eps": 1e-06,
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+ "rope_scaling": null,
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+ "rope_theta": 600000,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.36.0",
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+ "use_cache": true,
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+ "use_bias": false,
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+ "use_qkv_bias": false,
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+ "vocab_size": 126464,
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+ "output_router_logits": false,
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+ "embedding_dropout": 0.0,
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+ "norm_head": true,
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+ "norm_softmax": false,
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+ "output_dropout": 0.0
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+ }
configuration_bailing_moe.py ADDED
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+ """ Bailing MoE model configuration """
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+
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+ from transformers.configuration_utils import PretrainedConfig
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+
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+
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+ class BailingMoeConfig(PretrainedConfig):
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+ model_type = "bailing_moe"
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+
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+ def __init__(
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+ self,
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+ vocab_size=30592,
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+ hidden_size=1024,
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+ intermediate_size=None,
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+ num_hidden_layers=24,
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+ num_attention_heads=16,
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+ num_key_value_heads=0,
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+ hidden_act="silu",
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+ use_qkv_bias=False, # bailing only
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+ use_bias=True, # bailing only
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+ rms_norm_eps=1e-05,
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+ norm_head=False, # bailing only
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+ tie_word_embeddings=False, # PretrainedConfig key, here change default value.
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+ embedding_dropout=0.1,
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+ attention_dropout=0.1,
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+ output_dropout=0.1,
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+ initializer_range=0.02,
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+ max_position_embeddings=16384,
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+ rope_theta=10000.0,
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+ use_cache=True,
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+ use_sliding_window=False,
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+ sliding_window=4096,
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+ max_window_layers=28,
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+ rope_scaling=None,
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+ pad_token_id=126081,
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+ num_experts=16,
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+ num_shared_experts=0,
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+ num_experts_per_tok=2,
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+ norm_topk_prob=True,
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+ moe_intermediate_size=None,
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+ first_k_dense_replace=0,
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+ head_dim=None,
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+ output_router_logits=False,
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+ **kwargs,
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+ ):
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+ self.num_hidden_layers = num_hidden_layers
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+ self.vocab_size = vocab_size
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+ self.hidden_size = hidden_size
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+ self.intermediate_size = intermediate_size
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+ self.num_attention_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.use_qkv_bias = use_qkv_bias
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+ self.use_bias = use_bias
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+ self.norm_head = norm_head
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+ self.rms_norm_eps = rms_norm_eps
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+ self.embedding_dropout = embedding_dropout
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+ self.attention_dropout = attention_dropout
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+ self.output_dropout = output_dropout
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+ self.initializer_range = initializer_range
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+ self.max_position_embeddings = max_position_embeddings
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+ self.rope_theta = rope_theta
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+ self.use_cache = use_cache
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+ self.use_sliding_window = use_sliding_window
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+ self.sliding_window = sliding_window
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+ self.max_window_layers = max_window_layers
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+ self.head_dim = head_dim
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+ self.rope_scaling = rope_scaling
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+
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+ # MoE configs
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+ self.num_experts = num_experts
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+ self.num_shared_experts = num_shared_experts
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+ self.num_experts_per_tok = num_experts_per_tok
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+ self.norm_topk_prob = norm_topk_prob
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+ self.moe_intermediate_size = moe_intermediate_size
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+ self.first_k_dense_replace = first_k_dense_replace
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+ self.output_router_logits = output_router_logits
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+
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+ super().__init__(pad_token_id=pad_token_id, tie_word_embeddings=tie_word_embeddings, **kwargs)
md5sums.txt ADDED
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