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from transformers.models.qwen2.configuration_qwen2 import Qwen2Config
class KimiAudioConfig(Qwen2Config):
def __init__(
self,
vocab_size=163840,
hidden_size=4096,
intermediate_size=11008,
num_hidden_layers=32,
num_attention_heads=32,
num_key_value_heads=None,
hidden_act="silu",
initializer_range=0.02,
rms_norm_eps=1e-6,
use_cache=True,
rope_theta=10000.0,
rope_scaling=None,
tie_word_embeddings=False,
kimia_mimo_layers: int = 6,
kimia_mimo_audiodelaytokens: int = 5,
kimia_mimo_transformer_from_layer_index: int = 21,
kimia_audio_output_vocab: int = 16896,
kimia_text_output_vocab: int = 152064,
num_audio_special_tokens: int = 512,
num_base_tokens: int = 151643,
kimia_token_offset: int = 152064,
use_whisper_feature: bool = True,
kimia_adaptor_input_dim: int = 5120,
kimia_media_begin: int = 151661,
kimia_media_end: int = 151663,
**kwargs,
):
super().__init__(
vocab_size=vocab_size,
hidden_size=hidden_size,
intermediate_size=intermediate_size,
num_hidden_layers=num_hidden_layers,
num_attention_heads=num_attention_heads,
num_key_value_heads=num_key_value_heads,
hidden_act=hidden_act,
initializer_range=initializer_range,
rms_norm_eps=rms_norm_eps,
use_cache=use_cache,
tie_word_embeddings=tie_word_embeddings,
rope_theta=rope_theta,
rope_scaling=rope_scaling,
**kwargs,
)
self.kimia_mimo_layers = kimia_mimo_layers
self.kimia_mimo_audiodelaytokens = kimia_mimo_audiodelaytokens
# vocab
self.kimia_mimo_transformer_from_layer_index = (
kimia_mimo_transformer_from_layer_index
)
self.kimia_audio_output_vocab = kimia_audio_output_vocab
self.kimia_text_output_vocab = kimia_text_output_vocab
self.num_audio_special_tokens = num_audio_special_tokens
self.num_base_tokens = num_base_tokens
self.kimia_token_offset = kimia_token_offset
self.use_whisper_feature = use_whisper_feature
self.kimia_adaptor_input_dim = kimia_adaptor_input_dim
# special tokens
self.kimia_media_begin = kimia_media_begin
self.kimia_media_end = kimia_media_end
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