genericdeag/monkey-user 🖼️🔢❓📝✓ → 🖼️

▶️ 34 runs 📅 Jan 2025 ⚙️ Cog 0.11.1

About

Example Output

Prompt:

"A minimalistic cartoon illustration, a small office with beige walls, a wooden shelf on the left containing a few books, a green potted plant, and a wastebasket, a black-framed picture on the wall labeled "FRIEND" with a red HAL 9000-like glowing eye, a therapist character sitting on a black rolling chair, holding a clipboard with "LOSS: 0.71" written on it, the therapist has a stick-figure-like body and neutral expression, across from them a blob-like anthropomorphic neural network with purple nodes and connecting lines, tired eyes, lying on a brown therapy couch, speech bubble saying "I am so tired of learning, everybody expects me to constantly improve but they never ask if I want to.""

Output

Performance Metrics

24.93s Prediction Time

24.96s Total Time

All Input Parameters

{
  "model": "dev",
  "width": 1440,
  "height": 1440,
  "prompt": "A minimalistic cartoon illustration, a small office with beige walls, a wooden shelf on the left containing a few books, a green potted plant, and a wastebasket, a black-framed picture on the wall labeled \"FRIEND\" with a red HAL 9000-like glowing eye, a therapist character sitting on a black rolling chair, holding a clipboard with \"LOSS: 0.71\" written on it, the therapist has a stick-figure-like body and neutral expression, across from them a blob-like anthropomorphic neural network with purple nodes and connecting lines, tired eyes, lying on a brown therapy couch, speech bubble saying \"I am so tired of learning, everybody expects me to constantly improve but they never ask if I want to.\"",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 4,
  "aspect_ratio": "4:3",
  "output_format": "jpg",
  "guidance_scale": 3,
  "output_quality": 92,
  "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

2025-01-22 12:56:02.358 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-22 12:56:02.359 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  98%|█████████▊| 298/304 [00:00<00:00, 2970.55it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2959.62it/s]
2025-01-22 12:56:02.462 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.1s
free=29065759637504
Downloading weights
2025-01-22T12:56:02Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmp3xx2glem/weights url=https://replicate.delivery/xezq/J0n0syZrnNLIMpU09gi5ECpIWsmQPj72R32C86zUgNI2W6BF/trained_model.tar
2025-01-22T12:56:03Z | INFO  | [ Complete ] dest=/tmp/tmp3xx2glem/weights size="172 MB" total_elapsed=1.228s url=https://replicate.delivery/xezq/J0n0syZrnNLIMpU09gi5ECpIWsmQPj72R32C86zUgNI2W6BF/trained_model.tar
Downloaded weights in 1.25s
2025-01-22 12:56:03.716 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/7ca10f6b1e996242
2025-01-22 12:56:03.789 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2025-01-22 12:56:03.789 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-22 12:56:03.790 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  93%|█████████▎| 283/304 [00:00<00:00, 2810.77it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2771.12it/s]
2025-01-22 12:56:03.900 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s
Using seed: 23215
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Total safe images: 4 out of 4

Version Details

Version ID: 9bbbfdfb57fccc75f26ed226e151011cf6e0942166fe6ced97fae0bdd4f97d9d
Version Created: January 22, 2025

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