zsxkib
/
flux-abstract-beings
Surrealist digital art featuring whimsical, anthropomorphic characters with exaggerated textures and vibrant color blocking
- Public
- 532 runs
-
H100
Prediction
zsxkib/flux-abstract-beings:dc2c4f9bIDq0vbkb727srm20cjdr8bb0xh98StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- indigo ABSRTBNGS abstract being knife head, purple background
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "indigo ABSRTBNGS abstract being knife head, purple background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/flux-abstract-beings:dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", { input: { model: "dev", prompt: "indigo ABSRTBNGS abstract being knife head, purple background", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/flux-abstract-beings:dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", input={ "model": "dev", "prompt": "indigo ABSRTBNGS abstract being knife head, purple background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", "input": { "model": "dev", "prompt": "indigo ABSRTBNGS abstract being knife head, purple background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-08T21:38:13.333781Z", "created_at": "2024-10-08T21:37:33.246000Z", "data_removed": false, "error": null, "id": "q0vbkb727srm20cjdr8bb0xh98", "input": { "model": "dev", "prompt": "indigo ABSRTBNGS abstract being knife head, purple background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 56934\nPrompt: indigo ABSRTBNGS abstract being knife head, purple background\n[!] txt2img mode\nUsing dev model\nfree=7419752054784\nDownloading weights\n2024-10-08T21:38:01Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp9zexi7aq/weights url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar\n2024-10-08T21:38:02Z | INFO | [ Complete ] dest=/tmp/tmp9zexi7aq/weights size=\"172 MB\" total_elapsed=1.771s url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar\nDownloaded weights in 1.80s\nLoaded LoRAs in 2.39s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:09, 2.88it/s]\n 7%|▋ | 2/28 [00:00<00:08, 3.21it/s]\n 11%|█ | 3/28 [00:00<00:08, 3.05it/s]\n 14%|█▍ | 4/28 [00:01<00:08, 2.98it/s]\n 18%|█▊ | 5/28 [00:01<00:07, 2.95it/s]\n 21%|██▏ | 6/28 [00:02<00:07, 2.92it/s]\n 25%|██▌ | 7/28 [00:02<00:07, 2.91it/s]\n 29%|██▊ | 8/28 [00:02<00:06, 2.90it/s]\n 32%|███▏ | 9/28 [00:03<00:06, 2.90it/s]\n 36%|███▌ | 10/28 [00:03<00:06, 2.89it/s]\n 39%|███▉ | 11/28 [00:03<00:05, 2.89it/s]\n 43%|████▎ | 12/28 [00:04<00:05, 2.89it/s]\n 46%|████▋ | 13/28 [00:04<00:05, 2.89it/s]\n 50%|█████ | 14/28 [00:04<00:04, 2.89it/s]\n 54%|█████▎ | 15/28 [00:05<00:04, 2.89it/s]\n 57%|█████▋ | 16/28 [00:05<00:04, 2.89it/s]\n 61%|██████ | 17/28 [00:05<00:03, 2.89it/s]\n 64%|██████▍ | 18/28 [00:06<00:03, 2.89it/s]\n 68%|██████▊ | 19/28 [00:06<00:03, 2.89it/s]\n 71%|███████▏ | 20/28 [00:06<00:02, 2.89it/s]\n 75%|███████▌ | 21/28 [00:07<00:02, 2.89it/s]\n 79%|███████▊ | 22/28 [00:07<00:02, 2.89it/s]\n 82%|████████▏ | 23/28 [00:07<00:01, 2.89it/s]\n 86%|████████▌ | 24/28 [00:08<00:01, 2.89it/s]\n 89%|████████▉ | 25/28 [00:08<00:01, 2.89it/s]\n 93%|█████████▎| 26/28 [00:08<00:00, 2.89it/s]\n 96%|█████████▋| 27/28 [00:09<00:00, 2.89it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.89it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.90it/s]", "metrics": { "predict_time": 12.378467436, "total_time": 40.087781 }, "output": [ "https://replicate.delivery/yhqm/mqwsoK8WtX76LhKfemPDTCtWSyvYgXH4eObpkTligLuLCrJnA/out-0.webp" ], "started_at": "2024-10-08T21:38:00.955313Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/q0vbkb727srm20cjdr8bb0xh98", "cancel": "https://api.replicate.com/v1/predictions/q0vbkb727srm20cjdr8bb0xh98/cancel" }, "version": "dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465" }Generated inUsing seed: 56934 Prompt: indigo ABSRTBNGS abstract being knife head, purple background [!] txt2img mode Using dev model free=7419752054784 Downloading weights 2024-10-08T21:38:01Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp9zexi7aq/weights url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar 2024-10-08T21:38:02Z | INFO | [ Complete ] dest=/tmp/tmp9zexi7aq/weights size="172 MB" total_elapsed=1.771s url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar Downloaded weights in 1.80s Loaded LoRAs in 2.39s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.88it/s] 7%|▋ | 2/28 [00:00<00:08, 3.21it/s] 11%|█ | 3/28 [00:00<00:08, 3.05it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.98it/s] 18%|█▊ | 5/28 [00:01<00:07, 2.95it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.92it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.91it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.90it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.90it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.89it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.89it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.89it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.89it/s] 50%|█████ | 14/28 [00:04<00:04, 2.89it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.89it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.89it/s] 61%|██████ | 17/28 [00:05<00:03, 2.89it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.89it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.89it/s] 71%|███████▏ | 20/28 [00:06<00:02, 2.89it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.89it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.89it/s] 82%|████████▏ | 23/28 [00:07<00:01, 2.89it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.89it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.89it/s] 93%|█████████▎| 26/28 [00:08<00:00, 2.89it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.89it/s] 100%|██████████| 28/28 [00:09<00:00, 2.89it/s] 100%|██████████| 28/28 [00:09<00:00, 2.90it/s]Prediction
zsxkib/flux-abstract-beings:dc2c4f9bInput
- model
- dev
- prompt
- ABSRTBNGS abstract interesting face, yellow background
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "ABSRTBNGS abstract interesting face, yellow background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/flux-abstract-beings:dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", { input: { model: "dev", prompt: "ABSRTBNGS abstract interesting face, yellow background", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/flux-abstract-beings:dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", input={ "model": "dev", "prompt": "ABSRTBNGS abstract interesting face, yellow background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", "input": { "model": "dev", "prompt": "ABSRTBNGS abstract interesting face, yellow background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-08T21:40:15.868599Z", "created_at": "2024-10-08T21:39:55.204000Z", "data_removed": false, "error": null, "id": "23bhwf0crhrm20cjdr9vn33df4", "input": { "model": "dev", "prompt": "ABSRTBNGS abstract interesting face, yellow background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 30274\nPrompt: ABSRTBNGS abstract interesting face, yellow background\n[!] txt2img mode\nUsing dev model\nfree=8849131999232\nDownloading weights\n2024-10-08T21:40:04Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpetcrfusg/weights url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar\n2024-10-08T21:40:05Z | INFO | [ Complete ] dest=/tmp/tmpetcrfusg/weights size=\"172 MB\" total_elapsed=1.102s url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar\nDownloaded weights in 1.13s\nLoaded LoRAs in 1.87s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:09, 2.88it/s]\n 7%|▋ | 2/28 [00:00<00:08, 3.22it/s]\n 11%|█ | 3/28 [00:00<00:08, 3.06it/s]\n 14%|█▍ | 4/28 [00:01<00:08, 2.99it/s]\n 18%|█▊ | 5/28 [00:01<00:07, 2.95it/s]\n 21%|██▏ | 6/28 [00:02<00:07, 2.93it/s]\n 25%|██▌ | 7/28 [00:02<00:07, 2.92it/s]\n 29%|██▊ | 8/28 [00:02<00:06, 2.91it/s]\n 32%|███▏ | 9/28 [00:03<00:06, 2.90it/s]\n 36%|███▌ | 10/28 [00:03<00:06, 2.90it/s]\n 39%|███▉ | 11/28 [00:03<00:05, 2.89it/s]\n 43%|████▎ | 12/28 [00:04<00:05, 2.89it/s]\n 46%|████▋ | 13/28 [00:04<00:05, 2.89it/s]\n 50%|█████ | 14/28 [00:04<00:04, 2.89it/s]\n 54%|█████▎ | 15/28 [00:05<00:04, 2.89it/s]\n 57%|█████▋ | 16/28 [00:05<00:04, 2.89it/s]\n 61%|██████ | 17/28 [00:05<00:03, 2.89it/s]\n 64%|██████▍ | 18/28 [00:06<00:03, 2.89it/s]\n 68%|██████▊ | 19/28 [00:06<00:03, 2.89it/s]\n 71%|███████▏ | 20/28 [00:06<00:02, 2.89it/s]\n 75%|███████▌ | 21/28 [00:07<00:02, 2.89it/s]\n 79%|███████▊ | 22/28 [00:07<00:02, 2.89it/s]\n 82%|████████▏ | 23/28 [00:07<00:01, 2.89it/s]\n 86%|████████▌ | 24/28 [00:08<00:01, 2.89it/s]\n 89%|████████▉ | 25/28 [00:08<00:01, 2.89it/s]\n 93%|█████████▎| 26/28 [00:08<00:00, 2.89it/s]\n 96%|█████████▋| 27/28 [00:09<00:00, 2.89it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.89it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.91it/s]", "metrics": { "predict_time": 11.846541447, "total_time": 20.664599 }, "output": [ "https://replicate.delivery/yhqm/RF8owlM9CP6XC9iY5uiEa2lSJ4cOCk5v8mgNBABF3F2vYN5E/out-0.webp" ], "started_at": "2024-10-08T21:40:04.022057Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/23bhwf0crhrm20cjdr9vn33df4", "cancel": "https://api.replicate.com/v1/predictions/23bhwf0crhrm20cjdr9vn33df4/cancel" }, "version": "dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465" }Generated inUsing seed: 30274 Prompt: ABSRTBNGS abstract interesting face, yellow background [!] txt2img mode Using dev model free=8849131999232 Downloading weights 2024-10-08T21:40:04Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpetcrfusg/weights url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar 2024-10-08T21:40:05Z | INFO | [ Complete ] dest=/tmp/tmpetcrfusg/weights size="172 MB" total_elapsed=1.102s url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar Downloaded weights in 1.13s Loaded LoRAs in 1.87s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.88it/s] 7%|▋ | 2/28 [00:00<00:08, 3.22it/s] 11%|█ | 3/28 [00:00<00:08, 3.06it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.99it/s] 18%|█▊ | 5/28 [00:01<00:07, 2.95it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.93it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.92it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.91it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.90it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.90it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.89it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.89it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.89it/s] 50%|█████ | 14/28 [00:04<00:04, 2.89it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.89it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.89it/s] 61%|██████ | 17/28 [00:05<00:03, 2.89it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.89it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.89it/s] 71%|███████▏ | 20/28 [00:06<00:02, 2.89it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.89it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.89it/s] 82%|████████▏ | 23/28 [00:07<00:01, 2.89it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.89it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.89it/s] 93%|█████████▎| 26/28 [00:08<00:00, 2.89it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.89it/s] 100%|██████████| 28/28 [00:09<00:00, 2.89it/s] 100%|██████████| 28/28 [00:09<00:00, 2.91it/s]Prediction
zsxkib/flux-abstract-beings:dc2c4f9bIDkbavmb9z0nrm00cjdrarcb3cj0StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- ABSRTBNGS abstract being, lot of blueberries face, cyan background
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "ABSRTBNGS abstract being, lot of blueberries face, cyan background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/flux-abstract-beings:dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", { input: { model: "dev", prompt: "ABSRTBNGS abstract being, lot of blueberries face, cyan background", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/flux-abstract-beings:dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", input={ "model": "dev", "prompt": "ABSRTBNGS abstract being, lot of blueberries face, cyan background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", "input": { "model": "dev", "prompt": "ABSRTBNGS abstract being, lot of blueberries face, cyan background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-08T21:42:31.026930Z", "created_at": "2024-10-08T21:42:19.141000Z", "data_removed": false, "error": null, "id": "kbavmb9z0nrm00cjdrarcb3cj0", "input": { "model": "dev", "prompt": "ABSRTBNGS abstract being, lot of blueberries face, cyan background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 31605\nPrompt: ABSRTBNGS abstract being, lot of blueberries face, cyan background\n[!] txt2img mode\nUsing dev model\nfree=6723272851456\nDownloading weights\n2024-10-08T21:42:19Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpsg9cp995/weights url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar\n2024-10-08T21:42:20Z | INFO | [ Complete ] dest=/tmp/tmpsg9cp995/weights size=\"172 MB\" total_elapsed=1.130s url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar\nDownloaded weights in 1.16s\nLoaded LoRAs in 1.81s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:09, 2.88it/s]\n 7%|▋ | 2/28 [00:00<00:08, 3.20it/s]\n 11%|█ | 3/28 [00:00<00:08, 3.04it/s]\n 14%|█▍ | 4/28 [00:01<00:08, 2.97it/s]\n 18%|█▊ | 5/28 [00:01<00:07, 2.94it/s]\n 21%|██▏ | 6/28 [00:02<00:07, 2.91it/s]\n 25%|██▌ | 7/28 [00:02<00:07, 2.90it/s]\n 29%|██▊ | 8/28 [00:02<00:06, 2.89it/s]\n 32%|███▏ | 9/28 [00:03<00:06, 2.89it/s]\n 36%|███▌ | 10/28 [00:03<00:06, 2.88it/s]\n 39%|███▉ | 11/28 [00:03<00:05, 2.88it/s]\n 43%|████▎ | 12/28 [00:04<00:05, 2.88it/s]\n 46%|████▋ | 13/28 [00:04<00:05, 2.87it/s]\n 50%|█████ | 14/28 [00:04<00:04, 2.87it/s]\n 54%|█████▎ | 15/28 [00:05<00:04, 2.87it/s]\n 57%|█████▋ | 16/28 [00:05<00:04, 2.87it/s]\n 61%|██████ | 17/28 [00:05<00:03, 2.88it/s]\n 64%|██████▍ | 18/28 [00:06<00:03, 2.88it/s]\n 68%|██████▊ | 19/28 [00:06<00:03, 2.88it/s]\n 71%|███████▏ | 20/28 [00:06<00:02, 2.88it/s]\n 75%|███████▌ | 21/28 [00:07<00:02, 2.88it/s]\n 79%|███████▊ | 22/28 [00:07<00:02, 2.88it/s]\n 82%|████████▏ | 23/28 [00:07<00:01, 2.88it/s]\n 86%|████████▌ | 24/28 [00:08<00:01, 2.88it/s]\n 89%|████████▉ | 25/28 [00:08<00:01, 2.88it/s]\n 93%|█████████▎| 26/28 [00:08<00:00, 2.88it/s]\n 96%|█████████▋| 27/28 [00:09<00:00, 2.88it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.88it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.89it/s]", "metrics": { "predict_time": 11.874019504, "total_time": 11.88593 }, "output": [ "https://replicate.delivery/yhqm/UBxYz5g2YFLhNN063eiPIKqGPCvXXclei721R89URGFHl1kTA/out-0.webp" ], "started_at": "2024-10-08T21:42:19.152911Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/kbavmb9z0nrm00cjdrarcb3cj0", "cancel": "https://api.replicate.com/v1/predictions/kbavmb9z0nrm00cjdrarcb3cj0/cancel" }, "version": "dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465" }Generated inUsing seed: 31605 Prompt: ABSRTBNGS abstract being, lot of blueberries face, cyan background [!] txt2img mode Using dev model free=6723272851456 Downloading weights 2024-10-08T21:42:19Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpsg9cp995/weights url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar 2024-10-08T21:42:20Z | INFO | [ Complete ] dest=/tmp/tmpsg9cp995/weights size="172 MB" total_elapsed=1.130s url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar Downloaded weights in 1.16s Loaded LoRAs in 1.81s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.88it/s] 7%|▋ | 2/28 [00:00<00:08, 3.20it/s] 11%|█ | 3/28 [00:00<00:08, 3.04it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.97it/s] 18%|█▊ | 5/28 [00:01<00:07, 2.94it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.91it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.90it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.89it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.89it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.88it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.88it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.88it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.87it/s] 50%|█████ | 14/28 [00:04<00:04, 2.87it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.87it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.87it/s] 61%|██████ | 17/28 [00:05<00:03, 2.88it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.88it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.88it/s] 71%|███████▏ | 20/28 [00:06<00:02, 2.88it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.88it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.88it/s] 82%|████████▏ | 23/28 [00:07<00:01, 2.88it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.88it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.88it/s] 93%|█████████▎| 26/28 [00:08<00:00, 2.88it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.88it/s] 100%|██████████| 28/28 [00:09<00:00, 2.88it/s] 100%|██████████| 28/28 [00:09<00:00, 2.89it/s]Prediction
zsxkib/flux-abstract-beings:dc2c4f9bIDnp9d6vsbvhrm20cjdrjvex9628StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- ABSRTBNGS abstract being evil spikeball bomb head, green background
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "ABSRTBNGS abstract being evil spikeball bomb head, green background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/flux-abstract-beings:dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", { input: { model: "dev", prompt: "ABSRTBNGS abstract being evil spikeball bomb head, green background", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/flux-abstract-beings:dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", input={ "model": "dev", "prompt": "ABSRTBNGS abstract being evil spikeball bomb head, green background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", "input": { "model": "dev", "prompt": "ABSRTBNGS abstract being evil spikeball bomb head, green background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-08T22:00:27.103692Z", "created_at": "2024-10-08T21:59:42.812000Z", "data_removed": false, "error": null, "id": "np9d6vsbvhrm20cjdrjvex9628", "input": { "model": "dev", "prompt": "ABSRTBNGS abstract being evil spikeball bomb head, green background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 20644\nPrompt: ABSRTBNGS abstract being evil spikeball bomb head, green background\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 0.60s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:09, 2.87it/s]\n 7%|▋ | 2/28 [00:00<00:08, 3.20it/s]\n 11%|█ | 3/28 [00:00<00:08, 3.04it/s]\n 14%|█▍ | 4/28 [00:01<00:08, 2.97it/s]\n 18%|█▊ | 5/28 [00:01<00:07, 2.93it/s]\n 21%|██▏ | 6/28 [00:02<00:07, 2.91it/s]\n 25%|██▌ | 7/28 [00:02<00:07, 2.90it/s]\n 29%|██▊ | 8/28 [00:02<00:06, 2.89it/s]\n 32%|███▏ | 9/28 [00:03<00:06, 2.88it/s]\n 36%|███▌ | 10/28 [00:03<00:06, 2.88it/s]\n 39%|███▉ | 11/28 [00:03<00:05, 2.88it/s]\n 43%|████▎ | 12/28 [00:04<00:05, 2.87it/s]\n 46%|████▋ | 13/28 [00:04<00:05, 2.87it/s]\n 50%|█████ | 14/28 [00:04<00:04, 2.87it/s]\n 54%|█████▎ | 15/28 [00:05<00:04, 2.87it/s]\n 57%|█████▋ | 16/28 [00:05<00:04, 2.87it/s]\n 61%|██████ | 17/28 [00:05<00:03, 2.87it/s]\n 64%|██████▍ | 18/28 [00:06<00:03, 2.87it/s]\n 68%|██████▊ | 19/28 [00:06<00:03, 2.87it/s]\n 71%|███████▏ | 20/28 [00:06<00:02, 2.87it/s]\n 75%|███████▌ | 21/28 [00:07<00:02, 2.87it/s]\n 79%|███████▊ | 22/28 [00:07<00:02, 2.87it/s]\n 82%|████████▏ | 23/28 [00:07<00:01, 2.87it/s]\n 86%|████████▌ | 24/28 [00:08<00:01, 2.87it/s]\n 89%|████████▉ | 25/28 [00:08<00:01, 2.87it/s]\n 93%|█████████▎| 26/28 [00:08<00:00, 2.87it/s]\n 96%|█████████▋| 27/28 [00:09<00:00, 2.87it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.87it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.89it/s]", "metrics": { "predict_time": 10.645293141, "total_time": 44.291692 }, "output": [ "https://replicate.delivery/yhqm/fM7HCA6QcU2QCiAaqfaIx6RyI3mQcwNVag2hZewtljJ2rrJnA/out-0.webp" ], "started_at": "2024-10-08T22:00:16.458399Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/np9d6vsbvhrm20cjdrjvex9628", "cancel": "https://api.replicate.com/v1/predictions/np9d6vsbvhrm20cjdrjvex9628/cancel" }, "version": "dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465" }Generated inUsing seed: 20644 Prompt: ABSRTBNGS abstract being evil spikeball bomb head, green background [!] txt2img mode Using dev model Loaded LoRAs in 0.60s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.87it/s] 7%|▋ | 2/28 [00:00<00:08, 3.20it/s] 11%|█ | 3/28 [00:00<00:08, 3.04it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.97it/s] 18%|█▊ | 5/28 [00:01<00:07, 2.93it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.91it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.90it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.89it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.88it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.88it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.88it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.87it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.87it/s] 50%|█████ | 14/28 [00:04<00:04, 2.87it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.87it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.87it/s] 61%|██████ | 17/28 [00:05<00:03, 2.87it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.87it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.87it/s] 71%|███████▏ | 20/28 [00:06<00:02, 2.87it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.87it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.87it/s] 82%|████████▏ | 23/28 [00:07<00:01, 2.87it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.87it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.87it/s] 93%|█████████▎| 26/28 [00:08<00:00, 2.87it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.87it/s] 100%|██████████| 28/28 [00:09<00:00, 2.87it/s] 100%|██████████| 28/28 [00:09<00:00, 2.89it/s]Prediction
zsxkib/flux-abstract-beings:dc2c4f9bIDzyd77ezzbnrm40cjdrpvyyghzcStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- yellow ABSRTBNGS abstract being strawberry head, rainbow body
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "yellow ABSRTBNGS abstract being strawberry head, rainbow body", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/flux-abstract-beings:dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", { input: { model: "dev", prompt: "yellow ABSRTBNGS abstract being strawberry head, rainbow body", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/flux-abstract-beings:dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", input={ "model": "dev", "prompt": "yellow ABSRTBNGS abstract being strawberry head, rainbow body", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run zsxkib/flux-abstract-beings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465", "input": { "model": "dev", "prompt": "yellow ABSRTBNGS abstract being strawberry head, rainbow body", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-08T22:09:36.458030Z", "created_at": "2024-10-08T22:09:21.245000Z", "data_removed": false, "error": null, "id": "zyd77ezzbnrm40cjdrpvyyghzc", "input": { "model": "dev", "prompt": "yellow ABSRTBNGS abstract being strawberry head, rainbow body", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 47889\nPrompt: yellow ABSRTBNGS abstract being strawberry head, rainbow body\n[!] txt2img mode\nUsing dev model\nfree=7398713856000\nDownloading weights\n2024-10-08T22:09:24Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp20wa8q2l/weights url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar\n2024-10-08T22:09:25Z | INFO | [ Complete ] dest=/tmp/tmp20wa8q2l/weights size=\"172 MB\" total_elapsed=1.464s url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar\nDownloaded weights in 1.49s\nLoaded LoRAs in 2.22s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:09, 2.89it/s]\n 7%|▋ | 2/28 [00:00<00:08, 3.22it/s]\n 11%|█ | 3/28 [00:00<00:08, 3.06it/s]\n 14%|█▍ | 4/28 [00:01<00:08, 2.99it/s]\n 18%|█▊ | 5/28 [00:01<00:07, 2.95it/s]\n 21%|██▏ | 6/28 [00:02<00:07, 2.93it/s]\n 25%|██▌ | 7/28 [00:02<00:07, 2.92it/s]\n 29%|██▊ | 8/28 [00:02<00:06, 2.91it/s]\n 32%|███▏ | 9/28 [00:03<00:06, 2.90it/s]\n 36%|███▌ | 10/28 [00:03<00:06, 2.90it/s]\n 39%|███▉ | 11/28 [00:03<00:05, 2.89it/s]\n 43%|████▎ | 12/28 [00:04<00:05, 2.89it/s]\n 46%|████▋ | 13/28 [00:04<00:05, 2.89it/s]\n 50%|█████ | 14/28 [00:04<00:04, 2.89it/s]\n 54%|█████▎ | 15/28 [00:05<00:04, 2.89it/s]\n 57%|█████▋ | 16/28 [00:05<00:04, 2.89it/s]\n 61%|██████ | 17/28 [00:05<00:03, 2.89it/s]\n 64%|██████▍ | 18/28 [00:06<00:03, 2.89it/s]\n 68%|██████▊ | 19/28 [00:06<00:03, 2.89it/s]\n 71%|███████▏ | 20/28 [00:06<00:02, 2.89it/s]\n 75%|███████▌ | 21/28 [00:07<00:02, 2.89it/s]\n 79%|███████▊ | 22/28 [00:07<00:02, 2.89it/s]\n 82%|████████▏ | 23/28 [00:07<00:01, 2.89it/s]\n 86%|████████▌ | 24/28 [00:08<00:01, 2.89it/s]\n 89%|████████▉ | 25/28 [00:08<00:01, 2.89it/s]\n 93%|█████████▎| 26/28 [00:08<00:00, 2.89it/s]\n 96%|█████████▋| 27/28 [00:09<00:00, 2.89it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.89it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.91it/s]", "metrics": { "predict_time": 12.199309902, "total_time": 15.21303 }, "output": [ "https://replicate.delivery/yhqm/fYR77LuVdjVNNSqLPfzokXwzwttqTecMfGCI8fD8P3NB0vmcC/out-0.webp" ], "started_at": "2024-10-08T22:09:24.258720Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zyd77ezzbnrm40cjdrpvyyghzc", "cancel": "https://api.replicate.com/v1/predictions/zyd77ezzbnrm40cjdrpvyyghzc/cancel" }, "version": "dc2c4f9b24af51176806636dad87130aebe826d9610f57c4e5ab842e02ca8465" }Generated inUsing seed: 47889 Prompt: yellow ABSRTBNGS abstract being strawberry head, rainbow body [!] txt2img mode Using dev model free=7398713856000 Downloading weights 2024-10-08T22:09:24Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp20wa8q2l/weights url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar 2024-10-08T22:09:25Z | INFO | [ Complete ] dest=/tmp/tmp20wa8q2l/weights size="172 MB" total_elapsed=1.464s url=https://replicate.delivery/yhqm/e9Jm2ZXqCGRmJKrbStkte2DReI4M7JwiJWfInydZVuTfOamcC/trained_model.tar Downloaded weights in 1.49s Loaded LoRAs in 2.22s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.89it/s] 7%|▋ | 2/28 [00:00<00:08, 3.22it/s] 11%|█ | 3/28 [00:00<00:08, 3.06it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.99it/s] 18%|█▊ | 5/28 [00:01<00:07, 2.95it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.93it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.92it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.91it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.90it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.90it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.89it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.89it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.89it/s] 50%|█████ | 14/28 [00:04<00:04, 2.89it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.89it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.89it/s] 61%|██████ | 17/28 [00:05<00:03, 2.89it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.89it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.89it/s] 71%|███████▏ | 20/28 [00:06<00:02, 2.89it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.89it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.89it/s] 82%|████████▏ | 23/28 [00:07<00:01, 2.89it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.89it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.89it/s] 93%|█████████▎| 26/28 [00:08<00:00, 2.89it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.89it/s] 100%|██████████| 28/28 [00:09<00:00, 2.89it/s] 100%|██████████| 28/28 [00:09<00:00, 2.91it/s]
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