Model Info and links

https://huggingface.co/circlestone-labs/Anima

Test 0 - Seed and guidance

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

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.

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.

CFG4.5, STEP50	Seed: 1620085323	Seed:1931701040	Seed:4075624134	Seed:2736029172
Bookshop girl
Face and hand
Legs and shoes

Test 1 - Bookstore

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

285H Time: 2m 26.69s | total 151.26 pipeline 146.65 preview 3.29 callback 0.98 | GPU 10654 MB 8% | RAM 22.38 GB 18%

	5	10	20	30	40	50	100
CFG1
CFG2
CFG3
CFG4
CFG5
CFG6
CFG8

Test 2 - Face and hands

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.

285H Time: 2m 40.12s | total 170.54 pipeline 160.07 preview 9.08 callback 1.06 | GPU 10654 MB 8% | RAM 22.48 GB 18%

	8	16	32	64
CFG3
CFG4
CFG4.5
CFG4.75
CFG5
CFG6

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.

	8	16	32	64
CFG3
CFG4
CFG4.5
CFG5
CFG5.5
CFG6

Test 4 - Other model covers

Test 5 - Other prompts

Test 6 - Optional find the cover

Test 7 - Empty prompts

seed:1	seed:2	seed:3	seed:4	seed:5

seed:6	seed:7	seed:8	seed:9	seed:10

seed:21	seed:42	seed:68	seed:324	seed:2026

System Info

Tue Feb  3 12:50:13 2026
Backend: ipex Pipeline: native Memory optimization: none Cross-attention: Scaled-Dot-Product
app: sdnext.git updated: 2026-02-02 hash: c7ecba67c tag:  tags:  url: https://github.com/liutyi/sdnext/tree/pytorch
arch: x86_64 cpu: x86_64 system: Linux release: 6.17.0-8-generic
python: 3.12.3 Pytorch: 2.10.0+xpu
device: Intel(R) Arc(TM) Graphics (1) ipex: 
ram: free:112.69 used:10.38 total:123.07
xformers: diffusers: 0.37.0.dev0 transformers: 4.57.5
active: xpu dtype: torch.bfloat16 vae: torch.bfloat16 unet: torch.bfloat16
base: CalamitousFelicitousness/Anima-sdnext-diffusers refiner: none vae: none te: none unet: none
ipex native none Scaled-Dot-Product

App config

Model metadata

CalamitousFelicitousness/Anima-sdnext-diffusers

Module	Class	Device	Dtype	Quant	Params	Modules	Config
text_encoder	Qwen3Model	xpu:0	torch.bfloat16	None	596049920	425	Qwen3Config { "architectures": [ "Qwen3Model" ], "attention_bias": false, "attention_dropout": 0.0, "dtype": "bfloat16", "head_dim": 128, "hidden_act": "silu", "hidden_size": 1024, "initializer_range": 0.02, "intermediate_size": 3072, "layer_types": [ "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention" ], "max_position_embeddings": 32768, "max_window_layers": 28, "model_type": "qwen3", "num_attention_heads": 16, "num_hidden_layers": 28, "num_key_value_heads": 8, "rms_norm_eps": 1e-06, "rope_scaling": null, "rope_theta": 1000000.0, "sliding_window": null, "tie_word_embeddings": false, "transformers_version": "4.57.5", "use_cache": false, "use_sliding_window": false, "vocab_size": 151936 }
tokenizer	Qwen2TokenizerFast	None	None	None	0	0	None
t5_tokenizer	T5TokenizerFast	None	None	None	0	0	None
llm_adapter	AnimaLLMAdapter	xpu:0	torch.bfloat16	None	134663680	139	FrozenDict({'source_dim': 1024, 'target_dim': 1024, 'model_dim': 1024, 'num_layers': 6, 'num_heads': 16, 'mlp_ratio': 4.0, 'vocab_size': 32128, 'use_self_attn': True, '_class_name': 'AnimaLLMAdapter', '_diffusers_version': '0.37.0', '_name_or_path': 'CalamitousFelicitousness/Anima-sdnext-diffusers'})
transformer	CosmosTransformer3DModel	xpu:0	torch.bfloat16	None	1956405248	1138	FrozenDict({'in_channels': 16, 'out_channels': 16, 'num_attention_heads': 16, 'attention_head_dim': 128, 'num_layers': 28, 'mlp_ratio': 4.0, 'text_embed_dim': 1024, 'adaln_lora_dim': 256, 'max_size': [128, 240, 240], 'patch_size': [1, 2, 2], 'rope_scale': [1.0, 4.0, 4.0], 'concat_padding_mask': True, 'extra_pos_embed_type': None, 'use_crossattn_projection': False, 'crossattn_proj_in_channels': 1024, 'encoder_hidden_states_channels': 1024, '_use_default_values': ['use_crossattn_projection', 'crossattn_proj_in_channels', 'encoder_hidden_states_channels'], '_class_name': 'CosmosTransformer3DModel', '_diffusers_version': '0.37.0', '_name_or_path': 'CalamitousFelicitousness/Anima-sdnext-diffusers'})
vae	AutoencoderKLWan	xpu:0	torch.bfloat16	None	126892531	260	FrozenDict({'base_dim': 96, 'decoder_base_dim': None, '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], 'is_residual': False, 'in_channels': 3, 'out_channels': 3, 'patch_size': None, 'scale_factor_temporal': 4, 'scale_factor_spatial': 8, '_use_default_values': ['is_residual', 'decoder_base_dim', 'in_channels', 'patch_size', 'out_channels', 'scale_factor_spatial', 'scale_factor_temporal'], '_class_name': 'AutoencoderKLWan', '_diffusers_version': '0.33.0.dev0', '_name_or_path': '/mnt/models/Diffusers/models--CalamitousFelicitousness--Anima-sdnext-diffusers/snapshots/587e3941c37ace6234f9c0daa5c908408652870a/vae'})
scheduler	FlowMatchEulerDiscreteScheduler	None	None	None	0	0	FrozenDict({'num_train_timesteps': 1000, 'shift': 3.0, 'use_dynamic_shifting': False, 'base_shift': 0.5, 'max_shift': 1.15, 'base_image_seq_len': 256, 'max_image_seq_len': 4096, 'invert_sigmas': False, 'shift_terminal': None, 'use_karras_sigmas': False, 'use_exponential_sigmas': False, 'use_beta_sigmas': False, 'time_shift_type': 'exponential', 'stochastic_sampling': False, '_use_default_values': ['time_shift_type', 'max_image_seq_len', 'shift_terminal', 'use_beta_sigmas', 'base_image_seq_len', 'use_exponential_sigmas', 'max_shift', 'use_dynamic_shifting', 'use_karras_sigmas', 'stochastic_sampling', 'base_shift', 'invert_sigmas'], '_class_name': 'FlowMatchEulerDiscreteScheduler', '_diffusers_version': '0.37.0'})