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refine code

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Artiprocher
2025-07-29 20:02:34 +08:00
parent 03c8fd5e61
commit 87ab7d020b
3 changed files with 60 additions and 5 deletions
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61
diffsynth/models/nexus_gen_projector.py
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@@ -253,11 +253,66 @@ class Qwen2_5_VLDecoderLayer(nn.Module):
class NexusGenImageEmbeddingMerger(nn.Module):
def __init__(self, model_path="models/DiffSynth-Studio/Nexus-GenV2", num_layers=1, out_channel=4096, expand_ratio=4, device='cpu'):
def __init__(self, num_layers=1, out_channel=4096, expand_ratio=4, device='cpu'):
super().__init__()
from transformers import AutoConfig
from transformers import Qwen2_5_VLConfig
from transformers.activations import ACT2FN
config = AutoConfig.from_pretrained(model_path)
config = Qwen2_5_VLConfig(**{
"_name_or_path": "DiffSynth-Studio/Nexus-GenV2",
"architectures": [
"Qwen2_5_VLForConditionalGeneration"
],
"attention_dropout": 0.0,
"auto_map": {
"AutoConfig": "configuration_qwen2_5_vl.Qwen2_5_VLConfig",
"AutoModel": "modeling_qwen2_5_vl.Qwen2_5_VLModel",
"AutoModelForCausalLM": "modeling_qwen2_5_vl.Qwen2_5_VLForConditionalGeneration"
},
"bos_token_id": 151643,
"eos_token_id": 151645,
"hidden_act": "silu",
"hidden_size": 3584,
"image_token_id": 151655,
"initializer_range": 0.02,
"intermediate_size": 18944,
"max_position_embeddings": 128000,
"max_window_layers": 28,
"model_type": "qwen2_5_vl",
"num_attention_heads": 28,
"num_hidden_layers": 28,
"num_key_value_heads": 4,
"pad_token_id": 151643,
"rms_norm_eps": 1e-06,
"rope_scaling": {
"mrope_section": [
16,
24,
24
],
"rope_type": "default",
"type": "default"
},
"rope_theta": 1000000.0,
"sliding_window": 32768,
"tie_word_embeddings": False,
"torch_dtype": "bfloat16",
"transformers_version": "4.49.0",
"use_cache": False,
"use_sliding_window": False,
"video_token_id": 151656,
"vision_config": {
"hidden_size": 1280,
"in_chans": 3,
"model_type": "qwen2_5_vl",
"spatial_patch_size": 14,
"tokens_per_second": 2,
"torch_dtype": "bfloat16"
},
"vision_end_token_id": 151653,
"vision_start_token_id": 151652,
"vision_token_id": 151654,
"vocab_size": 152064
})
self.config = config
self.num_layers = num_layers
self.layers = nn.ModuleList([Qwen2_5_VLDecoderLayer(config, layer_idx) for layer_idx in range(num_layers)])