doobls-ai/golliersrasse-selfcaptioned 🖼️🔢❓📝✓ → 🖼️

▶️ 49 runs 📅 Dec 2024 ⚙️ Cog 0.11.1

About

Example Output

Prompt:

golliersrasse Imagine a modern office room designed for productivity and comfort. A central desk faces the entrance, equipped with a computer setup: a monitor, keyboard, and mouse. To the right of the monitor, there’s a pen holder filled with writing tools and a notepad beside it. On the left, a framed photograph adds a personal touch, while a desk lamp in the far-left corner provides focused lighting.

Within arm’s reach on the right side stands a filing cabinet, while a nearby printer station includes a paper supply shelf. A cozy seating area with two chairs and a small coffee table is positioned in the opposite corner from the entrance. Against the left wall, a bookshelf displays books and decorative items. Behind the desk, a mounted whiteboard offers space for quick notes and brainstorming sessions.

Output

Performance Metrics

22.81s Prediction Time

37.59s Total Time

All Input Parameters

{
  "model": "dev",
  "prompt": "golliersrasse Imagine a modern office room designed for productivity and comfort. A central desk faces the entrance, equipped with a computer setup: a monitor, keyboard, and mouse. To the right of the monitor, there’s a pen holder filled with writing tools and a notepad beside it. On the left, a framed photograph adds a personal touch, while a desk lamp in the far-left corner provides focused lighting.\n\nWithin arm’s reach on the right side stands a filing cabinet, while a nearby printer station includes a paper supply shelf. A cozy seating area with two chairs and a small coffee table is positioned in the opposite corner from the entrance. Against the left wall, a bookshelf displays books and decorative items. Behind the desk, a mounted whiteboard offers space for quick notes and brainstorming sessions.",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 3,
  "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

2024-12-11 07:21:35.118 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-11 07:21:35.119 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  92%|█████████▏| 281/304 [00:00<00:00, 2800.11it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2681.05it/s]
2024-12-11 07:21:35.232 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s
free=28928929992704
Downloading weights
2024-12-11T07:21:35Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmp_s58sdye/weights url=https://replicate.delivery/xezq/45jFefGsuPsV60nRAfff5gIE6xNO5fejpbRMbRal55W1H8z8JA/trained_model.tar
2024-12-11T07:21:39Z | INFO  | [ Complete ] dest=/tmp/tmp_s58sdye/weights size="172 MB" total_elapsed=4.213s url=https://replicate.delivery/xezq/45jFefGsuPsV60nRAfff5gIE6xNO5fejpbRMbRal55W1H8z8JA/trained_model.tar
Downloaded weights in 4.24s
2024-12-11 07:21:39.472 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/b2a87e8999153267
2024-12-11 07:21:39.547 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2024-12-11 07:21:39.547 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-11 07:21:39.548 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  92%|█████████▏| 281/304 [00:00<00:00, 2802.59it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2683.41it/s]
2024-12-11 07:21:39.661 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s
Using seed: 9073
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Total safe images: 3 out of 3

Version Details

Version ID: 7d2bc783d7bf478a05dcae34e334753d840ce79495df1a8560e0dc1851223a0d
Version Created: December 10, 2024

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