Model Info and links
https://huggingface.co/baidu/ERNIE-Image-Turbo
| Code Block |
|---|
import torch
from diffusers import ErnieImagePipeline
pipe = ErnieImagePipeline.from_pretrained(
"Baidu/ERNIE-Image-Turbo",
torch_dtype=torch.bfloat16,
).to("cuda")
image = pipe(
prompt="This is a photograph depicting an urban street scene. Shot at eye level, it shows a covered pedestrian or commercial street. Slightly below the center of the frame, a cyclist rides away from the camera toward the background, appearing as a dark silhouette against backlighting with indistinct details. The ground is paved with regular square tiles, bisected by a prominent tactile paving strip running through the scene, whose raised textures are clearly visible under the light. Light streams in diagonally from the right side of the frame, creating a strong backlight effect with a distinct Tyndall effect—visible light beams illuminating dust or vapor in the air and casting long shadows across the street. Several pedestrians appear on the left side and in the distance, some with their backs to the camera and others walking sideways, all rendered as silhouettes or semi-silhouettes. The overall color palette is warm, dominated by golden yellows and dark browns, evoking the atmosphere of dusk or early morning.",
height=1264,
width=848,
num_inference_steps=8,
guidance_scale=1.0,
use_pe=True # use prompt enhancer
).images[0]
image.save("output.png")
|
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.
| CFG 1, STEP 8 | 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
| 2 | 4 | 6 | 8 | 12 | |
|---|---|---|---|---|---|
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.
| 2 | 4 | 6 | 8 | 12 | |
|---|---|---|---|---|---|
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.
| 2 | 4 | 6 | 8 | 12 | |
|---|---|---|---|---|---|
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.
Runtime: App: SD.Next| Version: bed2bc3| Pipeline: ErnieImagePipeline| Operations: txt2img
Parameters: Steps: 6| Size: 1024x1024| Scheduler: FlowMatchEulerDiscreteScheduler| Seed: 2736029172| CFG scale: 1| Model: ERNIE-Image-Turbo
285H Time: 1m 25.59s | total 111.78 pipeline 85.56 preview 25.22 sync 0.71 | GPU 29392 MB 23% | RAM 40.93 GB 33%
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
| Code Block |
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Diffusers/baidu/ERNIE-Image-Turbo [54f8a75695] app: sdnext.git updated: 2026-06-28 hash: bed2bc36a tag: tags: url: https://github.com/liutyi/sdnext/tree/pytorch arch: x86_64 cpu: x86_64 system: Linux release: 6.17.0-35-generic python: 3.12.3 Torch: 2.11.0+xpu device: Intel(R) Arc(TM) Graphics (1) ram: free:115.51 used:9.82 total:125.32 xformers: diffusers: 0.39.0.dev0 transformers: 5.13.0.dev0 active: xpu dtype: torch.bfloat16 vae: torch.bfloat16 unet: torch.bfloat16 base: Diffusers/baidu/ERNIE-Image-Turbo [54f8a75695] refiner: none vae: none te: none unet: none Backend: ipex Pipeline: native Memory optimization: none Cross-attention: Scaled-Dot-Product |
App config
| Code Block |
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{
"diffusers_offload_mode": "none",
"sd_checkpoint_hash": null,
"sd_model_checkpoint": "Diffusers/baidu/ERNIE-Image-Turbo [54f8a75695]"
} |
Model metadata
Diffusers/baidu/ERNIE-Image-Turbo [54f8a75695]
| Module | Class | Device | Dtype | Quant | Params | Modules | Config |
|---|---|---|---|---|---|---|---|
| transformer | ErnieImageTransformer2DModel | xpu:0 | torch.bfloat16 | None | 8033490048 | 558 | FrozenDict({'hidden_size': 4096, 'num_attention_heads': 32, 'num_layers': 36, 'ffn_hidden_size': 12288, 'in_channels': 128, 'out_channels': 128, 'patch_size': 1, 'text_in_dim': 3072, 'rope_theta': 256, 'rope_axes_dim': [32, 48, 48], 'eps': 1e-06, 'qk_layernorm': True, '_class_name': 'ErnieImageTransformer2DModel', '_diffusers_version': '0.36.0', 'lora_rank': 4, 'use_lora': False, '_name_or_path': 'baidu/ERNIE-Image-Turbo'}) |
| vae | AutoencoderKLFlux2 | xpu:0 | torch.bfloat16 | None | 84046115 | 244 | FrozenDict({'in_channels': 3, 'out_channels': 3, 'down_block_types': ['DownEncoderBlock2D', 'DownEncoderBlock2D', 'DownEncoderBlock2D', 'DownEncoderBlock2D'], 'up_block_types': ['UpDecoderBlock2D', 'UpDecoderBlock2D', 'UpDecoderBlock2D', 'UpDecoderBlock2D'], 'block_out_channels': [128, 256, 512, 512], 'decoder_block_out_channels': None, 'layers_per_block': 2, 'act_fn': 'silu', 'latent_channels': 32, 'norm_num_groups': 32, 'sample_size': 1024, 'force_upcast': True, 'use_quant_conv': True, 'use_post_quant_conv': True, 'mid_block_add_attention': True, 'batch_norm_eps': 0.0001, 'batch_norm_momentum': 0.1, 'patch_size': [2, 2], '_use_default_values': ['decoder_block_out_channels'], '_class_name': 'AutoencoderKLFlux2', '_diffusers_version': '0.36.0', '_name_or_path': '/mnt/models/Diffusers/models--baidu--ERNIE-Image-Turbo/snapshots/bc68c81e2a1730a394d5fc9fae70713dee940140/vae'}) |
| text_encoder | Mistral3Model | xpu:0 | torch.bfloat16 | None | 3849090048 | 669 | Mistral3Config { "architectures": [ "Mistral3Model" ], "dtype": "bfloat16", "image_token_index": 10, "model_type": "mistral3", "multimodal_projector_bias": false, "projector_hidden_act": "gelu", "spatial_merge_size": 2, "text_config": { "attention_dropout": 0.0, "bos_token_id": 1, "dtype": "bfloat16", "eos_token_id": 2, "head_dim": 128, "hidden_act": "silu", "hidden_size": 3072, "initializer_range": 0.02, "intermediate_size": 9216, "max_position_embeddings": 262144, "model_type": "mistral", "num_attention_heads": 32, "num_hidden_layers": 26, "num_key_value_heads": 8, "pad_token_id": null, "rms_norm_eps": 1e-05, "rope_parameters": { "beta_fast": 32.0, "beta_slow": 1.0, "factor": 16.0, "llama_4_scaling_beta": 0.1, "mscale": 1.0, "mscale_all_dim": 1.0, "original_max_position_embeddings": 16384, "rope_theta": 1000000.0, "rope_type": "yarn", "type": "yarn" }, "sliding_window": null, "tie_word_embeddings": true, "use_cache": true, "vocab_size": 131072 }, "tie_word_embeddings": true, "transformers_version": "5.13.0.dev0", "vision_config": { "attention_dropout": 0.0, "dtype": "bfloat16", "head_dim": 64, "hidden_act": "silu", "hidden_size": 1024, "image_size": 1540, "initializer_range": 0.02, "intermediate_size": 4096, "model_type": "pixtral", "num_attention_heads": 16, "num_channels": 3, "num_hidden_layers": 24, "patch_size": 14, "rope_parameters": { "rope_theta": 10000.0, "rope_type": "default" } }, "vision_feature_layer": -1 } |
| tokenizer | TokenizersBackend | None | None | None | 0 | 0 | None |
| scheduler | FlowMatchEulerDiscreteScheduler | None | None | None | 0 | 0 | FrozenDict({'num_train_timesteps': 1000, 'shift': 4.0, '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, '_class_name': 'FlowMatchEulerDiscreteScheduler', '_diffusers_version': '0.36.0'}) |
| pe | NoneType | None | None | None | 0 | 0 | None |
| pe_tokenizer | TokenizersBackend | None | None | None | 0 | 0 | None |