# Copyright (c) Alibaba Cloud. # # This source code is licensed under the license found in the # LICENSE file in the root directory of this source tree. from transformers import PretrainedConfig class QWenConfig(PretrainedConfig): model_type = "qwen" keys_to_ignore_at_inference = ["past_key_values"] def __init__( self, vocab_size=151936, hidden_size=4096, num_hidden_layers=32, num_attention_heads=32, emb_dropout_prob=0.0, attn_dropout_prob=0.0, layer_norm_epsilon=1e-6, initializer_range=0.02, max_position_embeddings=8192, scale_attn_weights=True, use_cache=True, bf16=False, fp16=False, fp32=False, kv_channels=128, rotary_pct=1.0, rotary_emb_base=10000, use_dynamic_ntk=True, use_logn_attn=True, use_flash_attn="auto", use_triton="auto", intermediate_size=22016, no_bias=True, tie_word_embeddings=False, use_cache_quantization=False, use_cache_kernel=False, softmax_in_fp32=False, **kwargs, ): self.vocab_size = vocab_size self.hidden_size = hidden_size self.intermediate_size = intermediate_size self.num_hidden_layers = num_hidden_layers self.num_attention_heads = num_attention_heads self.emb_dropout_prob = emb_dropout_prob self.attn_dropout_prob = attn_dropout_prob self.layer_norm_epsilon = layer_norm_epsilon self.initializer_range = initializer_range self.scale_attn_weights = scale_attn_weights self.use_cache = use_cache self.max_position_embeddings = max_position_embeddings self.bf16 = bf16 self.fp16 = fp16 self.fp32 = fp32 self.kv_channels = kv_channels self.rotary_pct = rotary_pct self.rotary_emb_base = rotary_emb_base self.use_dynamic_ntk = use_dynamic_ntk self.use_logn_attn = use_logn_attn self.use_flash_attn = use_flash_attn self.use_triton = use_triton self.no_bias = no_bias self.use_cache_quantization = use_cache_quantization self.use_cache_kernel = use_cache_kernel self.softmax_in_fp32 = softmax_in_fp32 super().__init__( tie_word_embeddings=tie_word_embeddings, **kwargs )