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Artiprocher
2026-01-19 16:56:14 +08:00
parent ae52d93694
commit b6ccb362b9
18 changed files with 460 additions and 35 deletions
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95
diffsynth/models/z_image_text_encoder.py
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@@ -3,38 +3,71 @@ import torch
class ZImageTextEncoder(torch.nn.Module):
def __init__(self):
def __init__(self, model_size="4B"):
super().__init__()
config = Qwen3Config(**{
"architectures": [
"Qwen3ForCausalLM"
],
"attention_bias": False,
"attention_dropout": 0.0,
"bos_token_id": 151643,
"eos_token_id": 151645,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 2560,
"initializer_range": 0.02,
"intermediate_size": 9728,
"max_position_embeddings": 40960,
"max_window_layers": 36,
"model_type": "qwen3",
"num_attention_heads": 32,
"num_hidden_layers": 36,
"num_key_value_heads": 8,
"rms_norm_eps": 1e-06,
"rope_scaling": None,
"rope_theta": 1000000,
"sliding_window": None,
"tie_word_embeddings": True,
"torch_dtype": "bfloat16",
"transformers_version": "4.51.0",
"use_cache": True,
"use_sliding_window": False,
"vocab_size": 151936
})
config_dict = {
"4B": Qwen3Config(**{
"architectures": [
"Qwen3ForCausalLM"
],
"attention_bias": False,
"attention_dropout": 0.0,
"bos_token_id": 151643,
"eos_token_id": 151645,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 2560,
"initializer_range": 0.02,
"intermediate_size": 9728,
"max_position_embeddings": 40960,
"max_window_layers": 36,
"model_type": "qwen3",
"num_attention_heads": 32,
"num_hidden_layers": 36,
"num_key_value_heads": 8,
"rms_norm_eps": 1e-06,
"rope_scaling": None,
"rope_theta": 1000000,
"sliding_window": None,
"tie_word_embeddings": True,
"torch_dtype": "bfloat16",
"transformers_version": "4.51.0",
"use_cache": True,
"use_sliding_window": False,
"vocab_size": 151936
}),
"8B": Qwen3Config(**{
"architectures": [
"Qwen3ForCausalLM"
],
"attention_bias": False,
"attention_dropout": 0.0,
"bos_token_id": 151643,
"dtype": "bfloat16",
"eos_token_id": 151645,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 12288,
"max_position_embeddings": 40960,
"max_window_layers": 36,
"model_type": "qwen3",
"num_attention_heads": 32,
"num_hidden_layers": 36,
"num_key_value_heads": 8,
"rms_norm_eps": 1e-06,
"rope_scaling": None,
"rope_theta": 1000000,
"sliding_window": None,
"tie_word_embeddings": False,
"transformers_version": "4.56.1",
"use_cache": True,
"use_sliding_window": False,
"vocab_size": 151936
})
}
config = config_dict[model_size]
self.model = Qwen3Model(config)
def forward(self, *args, **kwargs):