Info
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Negative prompt have significant impact on image quality |
https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B-Diffusers
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Prompt: photorealistic girl in bookshop choosing the book in romantic stories shelf. smiling
Negative: Vibrant colors, overexposed, static, blurry details, subtitles, style, artwork, painting, image, still, overall grayish, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, distorted limbs, fingers fused together, static image, cluttered background, three legs, many people in the background, walking backwards.
Parameters: Steps: 50| Size: 1024x1024| Seed: 2736029172| CFG scale: 5| App: SD.Next| Version: 7644432| Pipeline: WanPipeline| Operations: txt2img| Model: Wan2.2-TI2V-5B-DiffusersTime
285H Time: 2m 52.36s | total 174.08 pipeline 172.32 te 1.38 | GPU 29768 MB 24% | RAM 38.68 GB 31%
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Test 2 - Face and hand
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Test 2 - Face and hand
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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CFG10
Test 3 - Legs
Prompt: Generate a photo of a woman's legs, with her feet crossed and wearing white high-heeled shoes with ribbons tied around her ankles. The shoes should have a pointed toe and a stiletto heel. The woman's legs should be smooth and tanned, with a slight sheen to them. The background should be a light gray color. The photo should be taken from a low angle, looking up at the woman's legs. The ribbons should be tied in a bow shape around the ankles. The shoes should have a red sole. The woman's legs should be slightly bent at the knee.
Parameters: Steps: 20| Size: 1024x1024| Seed: 1931701040| CFG scale: 6| App: SD.Next| Version: 34031f5| Pipeline: WanPipeline| Operations: txt2img| Model: Wan2.1-T2V-1.3B-Diffusers
Execution: Time: 3m 54.34s | total 439.88 pipeline 233.25 preview 194.33 te 5.20 offload 5.07 vae 1.20 decode 0.80 post 0.27 gc
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System info
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Negative: Vibrant colors, overexposed, static, blurry details, subtitles, style, artwork, painting, image, still, overall grayish, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, distorted limbs, fingers fused together, static image, cluttered background, three legs, many people in the background, walking backwards.
Parameters: Steps: 32| Size: 1024x1024| Seed: 1931701040| CFG scale: 4| App: SD.Next| Version: 7644432| Pipeline: WanPipeline| Operations: txt2img| Model: Wan2.2-TI2V-5B-Diffusers
Time: 1m 51.74s | total 113.37 pipeline 111.71 te 1.37 | GPU 29768 MB 24% | RAM 38.83 GB 32%
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Test 3 - Legs
Prompt: Generate a photo of a woman's legs, with her feet crossed and wearing white high-heeled shoes with ribbons tied around her ankles. The shoes should have a pointed toe and a stiletto heel. The woman's legs should be smooth and tanned, with a slight sheen to them. The background should be a light gray color. The photo should be taken from a low angle, looking up at the woman's legs. The ribbons should be tied in a bow shape around the ankles. The shoes should have a red sole. The woman's legs should be slightly bent at the knee.
Negative: Vibrant colors, overexposed, static, blurry details, subtitles, style, artwork, painting, image, still, overall grayish, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, distorted limbs, fingers fused together, static image, cluttered background, three legs, many people in the background, walking backwards.
Parameters: Steps: 32| Size: 1024x1024| Seed: 4075624134| CFG scale: 4| App: SD.Next| Version: 7644432| Pipeline: WanPipeline| Operations: txt2img| Model: Wan2.2-TI2V-5B-Diffusers
285H Time: 1m 51.81s | total 113.45 pipeline 111.76 te 1.38 | GPU 29768 MB 24% | RAM 38.76 GB 31%
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Test 4 - Other covers
1024px, CFG5, 20 steps, with standard negative prompt
Test 5 - some art prompts
System info
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app: sdnext.git updated: 2025-12-06 hash: 764443213 url: https://github.com/liutyi/sdnext/tree/pytorch
arch: x86_64 cpu: x86_64 system: Linux release: 6.17.0-7-generic
python: 3.12.3 Torch 2.9.1+xpu
ram: free:114.91 used:8.17 total:123.07
device: Intel(R) Arc(TM) Graphics (1) ipex:
xformers: diffusers: 0.36.0.dev0 transformers: 4.57.1
active: xpu dtype: torch.bfloat16 vae: torch.bfloat16 unet: torch.bfloat16
base: Diffusers/Wan-AI/Wan2.2-TI2V-5B-Diffusers [b8fff7315c] refiner: none vae: none te: none unet: none |
Config
| Code Block |
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{
"diffusers_version": "a1f36ee3ef4ae1bf98bd260e539197259aa981c1",
"sd_model_checkpoint": "Diffusers/Wan-AI/Wan2.2-TI2V-5B-Diffusers [b8fff7315c]",
"diffusers_offload_mode": "none",
"ui_request_timeout": 300000,
"huggingface_token": "hf_..FraU",
"sd_checkpoint_hash": null,
"model_wan_stage": "combined"
} |
Model info
Diffusers/Wan-AI/Wan2.2-TI2V-5B-Diffusers [b8fff7315c]...
Config
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{
} |
Model info
| Module | Class | Device | Dtype | Quant | Params | Modules | Config |
|---|---|---|---|---|---|---|---|
| vae | AutoencoderKLWan | xpu:0 | torch.bfloat16 | None | 704688668 | 272 | FrozenDict({'base_dim': 160, 'decoder_base_dim': 256, 'z_dim': 48, 'dim_mult': [1, 2, 4, 4], 'num_res_blocks': 2, 'attn_scales': [], 'temperal_downsample': [False, True, True], 'dropout': 0.0, 'latents_mean': [-0.2289, -0.0052, -0.1323, -0.2339, -0.2799, 0.0174, 0.1838, 0.1557, -0.1382, 0.0542, 0.2813, 0.0891, 0.157, -0.0098, 0.0375, -0.1825, -0.2246, -0.1207, -0.0698, 0.5109, 0.2665, -0.2108, -0.2158, 0.2502, -0.2055, -0.0322, 0.1109, 0.1567, -0.0729, 0.0899, -0.2799, -0.123, -0.0313, -0.1649, 0.0117, 0.0723, -0.2839, -0.2083, -0.052, 0.3748, 0.0152, 0.1957, 0.1433, -0.2944, 0.3573, -0.0548, -0.1681, -0.0667], 'latents_std': [0.4765, 1.0364, 0.4514, 1.1677, 0.5313, 0.499, 0.4818, 0.5013, 0.8158, 1.0344, 0.5894, 1.0901, 0.6885, 0.6165, 0.8454, 0.4978, 0.5759, 0.3523, 0.7135, 0.6804, 0.5833, 1.4146, 0.8986, 0.5659, 0.7069, 0.5338, 0.4889, 0.4917, 0.4069, 0.4999, 0.6866, 0.4093, 0.5709, 0.6065, 0.6415, 0.4944, 0.5726, 1.2042, 0.5458, 1.6887, 0.3971, 1.06, 0.3943, 0.5537, 0.5444, 0.4089, 0.7468, 0.7744], 'is_residual': True, 'in_channels': 12, 'out_channels': 12, 'patch_size': 2, 'scale_factor_temporal': 4, 'scale_factor_spatial': 16, '_class_name': 'AutoencoderKLWan', '_diffusers_version': '0.35.0.dev0', 'clip_output': False, '_name_or_path': '/mnt/models/Diffusers/models--Wan-AI--Wan2.2-TI2V-5B-Diffusers/snapshots/b8fff7315c768468a5333511427288870b2e9635/vae'}) |
| text_encoder | UMT5EncoderModel | xpu:0 | torch.bfloat16 | None | 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, "dtype": "bfloat16", "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", "transformers_version": "4.57.1", "use_cache": true, "vocab_size": 256384 } |
| tokenizer | T5TokenizerFast | None | None | None | 0 | 0 | None |
| transformer | WanTransformer3DModel | xpu:0 | torch.bfloat16 | None | 4999787712 | 858 | FrozenDict({'patch_size': [1, 2, 2], 'num_attention_heads': 24, 'attention_head_dim': 128, 'in_channels': 48, 'out_channels': 48, 'text_dim': 4096, 'freq_dim': 256, 'ffn_dim': 14336, 'num_layers': 30, '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, '_class_name': 'WanTransformer3DModel', '_diffusers_version': '0.35.0.dev0', '_name_or_path': 'Wan-AI/Wan2.2-TI2V-5B-Diffusers'}) |
| schedulerUniPCMultistepScheduler | UniPCMultistepScheduler | None | 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': 5.0, 'timestep_spacing': 'linspace', 'steps_offset': 0, 'final_sigmas_type': 'zero', 'rescale_betas_zero_snr': False, 'use_dynamic_shifting': False, 'time_shift_type': 'exponential', '_class_name': 'UniPCMultistepScheduler', '_diffusers_version': '0.35.0.dev0'}) |
| transformer_2 | NoneType | None | None | None | 0 | 0 | None |
| boundary_ratio | NoneType | None | None | None | 0 | 0 | None |
| expand_timesteps | bool | None | None | None | 0 | 0 | None |
...