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Prompt: photorealistic girl in bookshop choosing the book in romantic stories shelf. smiling

Parameters: Steps: 416| Size: 768x768| Seed: 1475741581| App: SD.Next| Version: 287c360| Pipeline: WanPipeline| Operations: txt2img| Model: Wan2.1-T2V-14B-Diffusers

Time: 1m 445m 34.85s 66s | total 184628.88 35 pipeline 104334.55 37 preview 55268.10 70 offload 11.65 85 vae 109.07 95 te 3.47 44 post 0.28 27 gc 0.27 26 | GPU 28460 29082 MB 22% 23% | RAM 40.36 37 GB 32%



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Prompt: Create a close-up photograph of a woman's face and hand, with her hand raised to her chin. She is wearing a white blazer and has a gold ring on her finger. Her nails are neatly manicured and her hair is pulled back into a low bun. She is smiling and has a radiant expression on her face. The background is a plain light gray color. The overall mood of the photo is elegant and sophisticated. The photo should have a soft, natural light and a slight warmth to it. The woman's hair is dark brown and pulled back into a low bun, with a few loose strands framing her face.

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System info


Code Block
app: sdnext.git updated: 2025-07-20 hash: 287c3600 url: https://github.com/vladmandic/sdnext.git/tree/dev
arch: x86_64 cpu: x86_64 system: Linux release: 6.14.0-24-generic
python: 3.12.3 Torch 2.7.1+xpu
device: Intel(R) Arc(TM) Graphics (1) ipex: 
xformers:  diffusers: 0.35.0.dev0 transformers: 4.53.2
active: xpu dtype: torch.bfloat16 vae: torch.bfloat16 unet: torch.bfloat16
base: Diffusers/Wan-AI/Wan2.1-T2V-14B-Diffusers [38ec498cb3] refiner: none vae: none te: none unet: none


Model info


Module Class Device DType Params Modules Config








vae

AutoencoderKLWan

xpu:0

torch.bfloat16

126892531

260

FrozenDict({'base_dim': 96, 'z_dim': 16, 'dim_mult': [1, 2, 4, 4], 'num_res_blocks': 2, 'attn_scales': [], 'temperal_downsample': [False, True, True], 'dropout': 0.0, 'latents_mean': [-0.7571, -0.7089, -0.9113, 0.1075, -0.1745, 0.9653, -0.1517, 1.5508, 0.4134, -0.0715, 0.5517, -0.3632, -0.1922, -0.9497, 0.2503, -0.2921], 'latents_std': [2.8184, 1.4541, 2.3275, 2.6558, 1.2196, 1.7708, 2.6052, 2.0743, 3.2687, 2.1526, 2.8652, 1.5579, 1.6382, 1.1253, 2.8251, 1.916], '_class_name': 'AutoencoderKLWan', '_diffusers_version': '0.33.0.dev0', '_name_or_path': '/mnt/models/Diffusers/models--Wan-AI--Wan2.1-T2V-14B-Diffusers/snapshots/38ec498cb3208fb688890f8cc7e94ede2cbd7f68/vae'})

text_encoder

UMT5EncoderModel

cpu

torch.bfloat16

5680910336

486

UMT5Config { "architectures": [ "UMT5EncoderModel" ], "classifier_dropout": 0.0, "d_ff": 10240, "d_kv": 64, "d_model": 4096, "decoder_start_token_id": 0, "dense_act_fn": "gelu_new", "dropout_rate": 0.1, "eos_token_id": 1, "feed_forward_proj": "gated-gelu", "initializer_factor": 1.0, "is_encoder_decoder": true, "is_gated_act": true, "layer_norm_epsilon": 1e-06, "model_type": "umt5", "num_decoder_layers": 24, "num_heads": 64, "num_layers": 24, "output_past": true, "pad_token_id": 0, "relative_attention_max_distance": 128, "relative_attention_num_buckets": 32, "scalable_attention": true, "tie_word_embeddings": false, "tokenizer_class": "T5Tokenizer", "torch_dtype": "bfloat16", "transformers_version": "4.53.2", "use_cache": true, "vocab_size": 256384 }

tokenizer

T5TokenizerFast

None

None

0

0

None

transformer

WanTransformer3DModel

cpu

torch.bfloat16

14288491584

1138

FrozenDict({'patch_size': [1, 2, 2], 'num_attention_heads': 40, 'attention_head_dim': 128, 'in_channels': 16, 'out_channels': 16, 'text_dim': 4096, 'freq_dim': 256, 'ffn_dim': 13824, 'num_layers': 40, 'cross_attn_norm': True, 'qk_norm': 'rms_norm_across_heads', 'eps': 1e-06, 'image_dim': None, 'added_kv_proj_dim': None, 'rope_max_seq_len': 1024, 'pos_embed_seq_len': None, '_use_default_values': ['pos_embed_seq_len'], '_class_name': 'WanTransformer3DModel', '_diffusers_version': '0.33.0.dev0', '_name_or_path': 'Wan-AI/Wan2.1-T2V-14B-Diffusers'})

scheduler

UniPCMultistepScheduler

None

None

0

0

FrozenDict({'num_train_timesteps': 1000, 'beta_start': 0.0001, 'beta_end': 0.02, 'beta_schedule': 'linear', 'trained_betas': None, 'solver_order': 2, 'prediction_type': 'flow_prediction', 'thresholding': False, 'dynamic_thresholding_ratio': 0.995, 'sample_max_value': 1.0, 'predict_x0': True, 'solver_type': 'bh2', 'lower_order_final': True, 'disable_corrector': [], 'solver_p': None, 'use_karras_sigmas': False, 'use_exponential_sigmas': False, 'use_beta_sigmas': False, 'use_flow_sigmas': True, 'flow_shift': 3.0, 'timestep_spacing': 'linspace', 'steps_offset': 0, 'final_sigmas_type': 'zero', 'rescale_betas_zero_snr': False, 'use_dynamic_shifting': False, 'time_shift_type': 'exponential', '_use_default_values': ['time_shift_type', 'use_dynamic_shifting'], '_class_name': 'UniPCMultistepScheduler', '_diffusers_version': '0.33.0.dev0'})

_name_or_path

str

None

None

0

0

None

_class_name

str

None

None

0

0

None

_diffusers_version

str

None

None

0

0

None