kikonessssss/oso_ricitos 🖼️🔢❓📝✓ → 🖼️
About
Example Output
Prompt:
"A hyper-realistic cinematic scene of a teddy bear oso_ricitos floating in space saying goodbye, surrounded by countless iridescent soap bubbles of various sizes. Some bubbles reflect distant stars, while others gently drift and pop, releasing tiny sparkling droplets. A soft trail of foam extends behind, dispersing in zero gravity. The International Space Station (ISS) looms in the background, partially illuminated by the glow of Earth below. Shooting stars and glowing particles move subtly, adding depth and motion to the surreal atmosphere"
Output
Performance Metrics
7.70s
Prediction Time
8.94s
Total Time
All Input Parameters
{
"model": "dev",
"prompt": "A hyper-realistic cinematic scene of a teddy bear oso_ricitos floating in space saying goodbye, surrounded by countless iridescent soap bubbles of various sizes. Some bubbles reflect distant stars, while others gently drift and pop, releasing tiny sparkling droplets. A soft trail of foam extends behind, dispersing in zero gravity. The International Space Station (ISS) looms in the background, partially illuminated by the glow of Earth below. Shooting stars and glowing particles move subtly, adding depth and motion to the surreal atmosphere",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "16:9",
"output_format": "jpg",
"guidance_scale": 3,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
Input Parameters
- mask
- Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
- seed
- Random seed. Set for reproducible generation
- image
- Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
- model
- Which model to run inference with. The dev model performs best with around 28 inference steps but the schnell model only needs 4 steps.
- width
- Width of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
- height
- Height of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
- prompt (required)
- Prompt for generated image. If you include the `trigger_word` used in the training process you are more likely to activate the trained object, style, or concept in the resulting image.
- go_fast
- Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16
- extra_lora
- Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
- lora_scale
- Determines how strongly the main LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
- megapixels
- Approximate number of megapixels for generated image
- num_outputs
- Number of outputs to generate
- aspect_ratio
- Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode
- output_format
- Format of the output images
- guidance_scale
- Guidance scale for the diffusion process. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5
- output_quality
- Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs
- prompt_strength
- Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image
- extra_lora_scale
- Determines how strongly the extra LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
- replicate_weights
- Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
- num_inference_steps
- Number of denoising steps. More steps can give more detailed images, but take longer.
- disable_safety_checker
- Disable safety checker for generated images.
Output Schema
Output
Example Execution Logs
Loaded LoRAs in 0.55s Using seed: 59639 Prompt: A hyper-realistic cinematic scene of a teddy bear oso_ricitos floating in space saying goodbye, surrounded by countless iridescent soap bubbles of various sizes. Some bubbles reflect distant stars, while others gently drift and pop, releasing tiny sparkling droplets. A soft trail of foam extends behind, dispersing in zero gravity. The International Space Station (ISS) looms in the background, partially illuminated by the glow of Earth below. Shooting stars and glowing particles move subtly, adding depth and motion to the surreal atmosphere [!] txt2img mode 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:06, 4.02it/s] 7%|▋ | 2/28 [00:00<00:05, 4.55it/s] 11%|█ | 3/28 [00:00<00:05, 4.29it/s] 14%|█▍ | 4/28 [00:00<00:05, 4.18it/s] 18%|█▊ | 5/28 [00:01<00:05, 4.13it/s] 21%|██▏ | 6/28 [00:01<00:05, 4.09it/s] 25%|██▌ | 7/28 [00:01<00:05, 4.06it/s] 29%|██▊ | 8/28 [00:01<00:04, 4.05it/s] 32%|███▏ | 9/28 [00:02<00:04, 4.03it/s] 36%|███▌ | 10/28 [00:02<00:04, 4.02it/s] 39%|███▉ | 11/28 [00:02<00:04, 4.02it/s] 43%|████▎ | 12/28 [00:02<00:03, 4.02it/s] 46%|████▋ | 13/28 [00:03<00:03, 4.02it/s] 50%|█████ | 14/28 [00:03<00:03, 4.03it/s] 54%|█████▎ | 15/28 [00:03<00:03, 4.03it/s] 57%|█████▋ | 16/28 [00:03<00:02, 4.02it/s] 61%|██████ | 17/28 [00:04<00:02, 4.02it/s] 64%|██████▍ | 18/28 [00:04<00:02, 4.01it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.99it/s] 71%|███████▏ | 20/28 [00:04<00:02, 3.98it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.99it/s] 79%|███████▊ | 22/28 [00:05<00:01, 4.01it/s] 82%|████████▏ | 23/28 [00:05<00:01, 4.01it/s] 86%|████████▌ | 24/28 [00:05<00:00, 4.01it/s] 89%|████████▉ | 25/28 [00:06<00:00, 4.01it/s] 93%|█████████▎| 26/28 [00:06<00:00, 4.02it/s] 96%|█████████▋| 27/28 [00:06<00:00, 4.02it/s] 100%|██████████| 28/28 [00:06<00:00, 4.02it/s] 100%|██████████| 28/28 [00:06<00:00, 4.04it/s] Total safe images: 1 out of 1
Version Details
- Version ID
0eef3805299f805f7b5af8f5bb05631010cb7173695acd76145db82dff7dae20- Version Created
- February 15, 2025