dgtlcorp/tero 🖼️🔢❓📝✓ → 🖼️

▶️ 71 runs 📅 Jan 2025 ⚙️ Cog 0.11.1

About

Example Output

Prompt:

A cozy winter coffee shop setting with warm, inviting lighting and rustic wooden interiors. Large windows frame a snowy outdoor scene, with frosted glass and soft natural light streaming in. The Blonde model, with a curvy, hourglass figure enhanced by a BBL, stands confidently near a wooden table. She is wearing beige tero leggings with fleece lining, paired with a long, tailored wool coat that drapes elegantly to mid-thigh. Beneath the coat, she wears a fitted turtleneck top, adding a sophisticated and polished touch to her winter ensemble. Stylish knee-high boots complement the look, ensuring practicality and flair for the colder months.

Her hand lightly rests on the back of the chair, while the other holds a steaming latte, exuding warmth and sophistication. Her face features soft, striking Latina features with long wavy hair cascading over her shoulders. The table beside her is decorated with a croissant on a plate, an open journal, and a branded coffee cup, completing the Starbucks-inspired ambiance. Warm caramel, cream, and forest green tones dominate the scene, with fairy lights and candles subtly glowing in the background. The beige tero leggings, designed for ultimate winter comfort, are the centerpiece, with lighting emphasizing their sleek fit and cozy fleece texture, perfectly balancing style and warm

Output

Performance Metrics

24.66s Prediction Time

24.77s Total Time

All Input Parameters

{
"model": "dev",
"prompt": "A cozy winter coffee shop setting with warm, inviting lighting and rustic wooden interiors. Large windows frame a snowy outdoor scene, with frosted glass and soft natural light streaming in. The Blonde model, with a curvy, hourglass figure enhanced by a BBL, stands confidently near a wooden table. She is wearing beige tero leggings with fleece lining, paired with a long, tailored wool coat that drapes elegantly to mid-thigh. Beneath the coat, she wears a fitted turtleneck top, adding a sophisticated and polished touch to her winter ensemble. Stylish knee-high boots complement the look, ensuring practicality and flair for the colder months.\n\nHer hand lightly rests on the back of the chair, while the other holds a steaming latte, exuding warmth and sophistication. Her face features soft, striking Latina features with long wavy hair cascading over her shoulders. The table beside her is decorated with a croissant on a plate, an open journal, and a branded coffee cup, completing the Starbucks-inspired ambiance. Warm caramel, cream, and forest green tones dominate the scene, with fairy lights and candles subtly glowing in the background. The beige tero leggings, designed for ultimate winter comfort, are the centerpiece, with lighting emphasizing their sleek fit and cozy fleece texture, perfectly balancing style and warm",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}

Input Parameters

mask Type: string: Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
seed Type: integer: Random seed. Set for reproducible generation
image Type: string: Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
model Default: dev: 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 Type: integerRange: 256 - 1440: 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 Type: integerRange: 256 - 1440: 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) Type: string: 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 Type: booleanDefault: false: Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16
extra_lora Type: string: 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 Type: numberDefault: 1Range: -1 - 3: 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 Default: 1: Approximate number of megapixels for generated image
num_outputs Type: integerDefault: 1Range: 1 - 4: Number of outputs to generate
aspect_ratio Default: 1:1: Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode
output_format Default: webp: Format of the output images
guidance_scale Type: numberDefault: 3Range: 0 - 10: 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 Type: integerDefault: 80Range: 0 - 100: 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 Type: numberDefault: 0.8Range: 0 - 1: Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image
extra_lora_scale Type: numberDefault: 1Range: -1 - 3: 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 Type: string: 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 Type: integerDefault: 28Range: 1 - 50: Number of denoising steps. More steps can give more detailed images, but take longer.
disable_safety_checker Type: booleanDefault: false: Disable safety checker for generated images.

Output Schema

Output

Type: array • Items Type: string • Items Format: uri

Example Execution Logs

2025-01-08 21:35:18.118 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-08 21:35:18.118 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  91%|█████████▏| 278/304 [00:00<00:00, 2773.11it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2662.86it/s]
2025-01-08 21:35:18.233 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s
2025-01-08 21:35:18.234 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/e3ec5ed2de2cd034
2025-01-08 21:35:18.349 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2025-01-08 21:35:18.349 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-08 21:35:18.349 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  91%|█████████▏| 278/304 [00:00<00:00, 2777.57it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2666.95it/s]
2025-01-08 21:35:18.463 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s
Using seed: 61022
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Total safe images: 4 out of 4

Version Details

Version ID: cc45fa51d9570923a2466eecb8544b44bc20a81f40a79f5d14e4de87cff0d897
Version Created: January 8, 2025

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