prunaai/ernie-image 🔢📝✓❓ → 🖼️
About
ERNIE-Image is an open text-to-image generation model developed by the ERNIE-Image team at Baidu
Example Output
Prompt:
"a beautiful landscape"
Output
Performance Metrics
34.58s
Prediction Time
34.59s
Total Time
All Input Parameters
{
"width": 1024,
"height": 1024,
"prompt": "a beautiful landscape",
"use_pe": true,
"num_outputs": 1,
"output_format": "jpg",
"guidance_scale": 4,
"output_quality": 80,
"num_inference_steps": 50
}
Input Parameters
- seed
- Random seed. Set for reproducible generation.
- width
- Width of the generated image. Best results come from the model-card recommended sizes.
- height
- Height of the generated image. Best results come from the model-card recommended sizes.
- prompt (required)
- Text prompt for image generation
- use_pe
- Enable the prompt enhancer recommended by the model card.
- num_outputs
- Number of output images to generate.
- output_format
- Format of the output image.
- guidance_scale
- Classifier-free guidance scale.
- output_quality
- Quality when saving the output image, from 0 to 100.
- num_inference_steps
- Number of inference steps.
Output Schema
Output
Example Execution Logs
Using seed: 719672883 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:27, 1.77it/s] 4%|▍ | 2/50 [00:00<00:21, 2.21it/s] 6%|▌ | 3/50 [00:01<00:23, 2.00it/s] 8%|▊ | 4/50 [00:02<00:24, 1.91it/s] 10%|█ | 5/50 [00:02<00:24, 1.86it/s] 12%|█▏ | 6/50 [00:03<00:23, 1.84it/s] 14%|█▍ | 7/50 [00:03<00:23, 1.82it/s] 16%|█▌ | 8/50 [00:04<00:23, 1.81it/s] 18%|█▊ | 9/50 [00:04<00:22, 1.80it/s] 20%|██ | 10/50 [00:05<00:22, 1.80it/s] 22%|██▏ | 11/50 [00:05<00:21, 1.80it/s] 24%|██▍ | 12/50 [00:06<00:21, 1.80it/s] 26%|██▌ | 13/50 [00:07<00:20, 1.79it/s] 28%|██▊ | 14/50 [00:07<00:20, 1.80it/s] 30%|███ | 15/50 [00:08<00:19, 1.79it/s] 32%|███▏ | 16/50 [00:08<00:18, 1.79it/s] 34%|███▍ | 17/50 [00:09<00:18, 1.79it/s] 36%|███▌ | 18/50 [00:09<00:17, 1.79it/s] 38%|███▊ | 19/50 [00:10<00:17, 1.79it/s] 40%|████ | 20/50 [00:10<00:16, 1.79it/s] 42%|████▏ | 21/50 [00:11<00:16, 1.79it/s] 44%|████▍ | 22/50 [00:12<00:15, 1.79it/s] 46%|████▌ | 23/50 [00:12<00:15, 1.79it/s] 48%|████▊ | 24/50 [00:13<00:14, 1.79it/s] 50%|█████ | 25/50 [00:13<00:13, 1.79it/s] 52%|█████▏ | 26/50 [00:14<00:13, 1.79it/s] 54%|█████▍ | 27/50 [00:14<00:12, 1.79it/s] 56%|█████▌ | 28/50 [00:15<00:12, 1.79it/s] 58%|█████▊ | 29/50 [00:16<00:11, 1.79it/s] 60%|██████ | 30/50 [00:16<00:11, 1.79it/s] 62%|██████▏ | 31/50 [00:17<00:10, 1.79it/s] 64%|██████▍ | 32/50 [00:17<00:10, 1.79it/s] 66%|██████▌ | 33/50 [00:18<00:09, 1.79it/s] 68%|██████▊ | 34/50 [00:18<00:08, 1.79it/s] 70%|███████ | 35/50 [00:19<00:08, 1.79it/s] 72%|███████▏ | 36/50 [00:19<00:07, 1.79it/s] 74%|███████▍ | 37/50 [00:20<00:07, 1.79it/s] 76%|███████▌ | 38/50 [00:21<00:06, 1.79it/s] 78%|███████▊ | 39/50 [00:21<00:06, 1.79it/s] 80%|████████ | 40/50 [00:22<00:05, 1.79it/s] 82%|████████▏ | 41/50 [00:22<00:05, 1.79it/s] 84%|████████▍ | 42/50 [00:23<00:04, 1.79it/s] 86%|████████▌ | 43/50 [00:23<00:03, 1.79it/s] 88%|████████▊ | 44/50 [00:24<00:03, 1.79it/s] 90%|█████████ | 45/50 [00:24<00:02, 1.79it/s] 92%|█████████▏| 46/50 [00:25<00:02, 1.79it/s] 94%|█████████▍| 47/50 [00:26<00:01, 1.79it/s] 96%|█████████▌| 48/50 [00:26<00:01, 1.79it/s] 98%|█████████▊| 49/50 [00:27<00:00, 1.79it/s] 100%|██████████| 50/50 [00:27<00:00, 1.79it/s] 100%|██████████| 50/50 [00:27<00:00, 1.80it/s]
Version Details
- Version ID
d5bfa4984edc317383025be5fd59a6a2d2b1992cf98bdddd788e5d5fa12a3ba4- Version Created
- April 14, 2026