prestoncreed / flux-spongebob
Fine-Tuned on spongebob environment/aesthetic images. Use "in the SPONGE world" to get best results.
- Public
- 183 runs
-
H100
Prediction
prestoncreed/flux-spongebob:d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550IDdjtav1bgn5rm20chrf5avhbkn8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Niagara falls on a beatiful sunny day, in the SPONGE world, with a SPONGE style airship in the sky flying above the waterfall
- 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": "Niagara falls on a beatiful sunny day, in the SPONGE world, with a SPONGE style airship in the sky flying above the waterfall", "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 replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run prestoncreed/flux-spongebob using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "prestoncreed/flux-spongebob:d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550", { input: { model: "dev", prompt: "Niagara falls on a beatiful sunny day, in the SPONGE world, with a SPONGE style airship in the sky flying above the waterfall", 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 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun prestoncreed/flux-spongebob using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "prestoncreed/flux-spongebob:d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550", input={ "model": "dev", "prompt": "Niagara falls on a beatiful sunny day, in the SPONGE world, with a SPONGE style airship in the sky flying above the waterfall", "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 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run prestoncreed/flux-spongebob 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": "prestoncreed/flux-spongebob:d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550", "input": { "model": "dev", "prompt": "Niagara falls on a beatiful sunny day, in the SPONGE world, with a SPONGE style airship in the sky flying above the waterfall", "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": "2024-09-05T20:05:31.078201Z", "created_at": "2024-09-05T20:05:09.929000Z", "data_removed": false, "error": null, "id": "djtav1bgn5rm20chrf5avhbkn8", "input": { "model": "dev", "prompt": "Niagara falls on a beatiful sunny day, in the SPONGE world, with a SPONGE style airship in the sky flying above the waterfall", "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: 26888\nPrompt: Niagara falls on a beatiful sunny day, in the SPONGE world, with a SPONGE style airship in the sky flying above the waterfall\n[!] txt2img mode\nUsing dev model\nfree=8403096502272\nDownloading weights\n2024-09-05T20:05:10Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp22d2_s5j/weights url=https://replicate.delivery/yhqm/xGJO9V4HWGawOlbbPju6wMUfTT1Y5FnDbh3TVMRrFh78P8sJA/trained_model.tar\n2024-09-05T20:05:13Z | INFO | [ Complete ] dest=/tmp/tmp22d2_s5j/weights size=\"172 MB\" total_elapsed=3.071s url=https://replicate.delivery/yhqm/xGJO9V4HWGawOlbbPju6wMUfTT1Y5FnDbh3TVMRrFh78P8sJA/trained_model.tar\nDownloaded weights in 3.10s\nLoaded LoRAs in 12.24s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.51it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.98it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.75it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.65it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.59it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.56it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.55it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.54it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.53it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.52it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.52it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.52it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.51it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.51it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.51it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.51it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.51it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.51it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.51it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.51it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.51it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.51it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.51it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.51it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.51it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.51it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.51it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.51it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.54it/s]", "metrics": { "predict_time": 20.722640441, "total_time": 21.149201 }, "output": [ "https://replicate.delivery/yhqm/Fs7ftHK4azSkSSEnorwGfeELnxozwrpnRUTqoo1QiHxVI4zmA/out-0.webp" ], "started_at": "2024-09-05T20:05:10.355560Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/djtav1bgn5rm20chrf5avhbkn8", "cancel": "https://api.replicate.com/v1/predictions/djtav1bgn5rm20chrf5avhbkn8/cancel" }, "version": "d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550" }Generated inUsing seed: 26888 Prompt: Niagara falls on a beatiful sunny day, in the SPONGE world, with a SPONGE style airship in the sky flying above the waterfall [!] txt2img mode Using dev model free=8403096502272 Downloading weights 2024-09-05T20:05:10Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp22d2_s5j/weights url=https://replicate.delivery/yhqm/xGJO9V4HWGawOlbbPju6wMUfTT1Y5FnDbh3TVMRrFh78P8sJA/trained_model.tar 2024-09-05T20:05:13Z | INFO | [ Complete ] dest=/tmp/tmp22d2_s5j/weights size="172 MB" total_elapsed=3.071s url=https://replicate.delivery/yhqm/xGJO9V4HWGawOlbbPju6wMUfTT1Y5FnDbh3TVMRrFh78P8sJA/trained_model.tar Downloaded weights in 3.10s Loaded LoRAs in 12.24s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.51it/s] 7%|▋ | 2/28 [00:00<00:06, 3.98it/s] 11%|█ | 3/28 [00:00<00:06, 3.75it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.65it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.59it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.56it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.55it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.54it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.53it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.52it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.52it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.52it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.51it/s] 50%|█████ | 14/28 [00:03<00:03, 3.51it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.51it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.51it/s] 61%|██████ | 17/28 [00:04<00:03, 3.51it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.51it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.51it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.51it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.51it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.51it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.51it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.51it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.51it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.51it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.51it/s] 100%|██████████| 28/28 [00:07<00:00, 3.51it/s] 100%|██████████| 28/28 [00:07<00:00, 3.54it/s]Prediction
prestoncreed/flux-spongebob:d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550IDx3r91chr21rm00chrfd9jhje3rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Surrealist SPONGE world style humanist classical portrait,
- 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": "Surrealist SPONGE world style humanist classical portrait,", "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 replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run prestoncreed/flux-spongebob using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "prestoncreed/flux-spongebob:d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550", { input: { model: "dev", prompt: "Surrealist SPONGE world style humanist classical portrait,", 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 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun prestoncreed/flux-spongebob using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "prestoncreed/flux-spongebob:d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550", input={ "model": "dev", "prompt": "Surrealist SPONGE world style humanist classical portrait,", "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 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run prestoncreed/flux-spongebob 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": "prestoncreed/flux-spongebob:d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550", "input": { "model": "dev", "prompt": "Surrealist SPONGE world style humanist classical portrait,", "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": "2024-09-05T20:23:37.517491Z", "created_at": "2024-09-05T20:22:24.016000Z", "data_removed": false, "error": null, "id": "x3r91chr21rm00chrfd9jhje3r", "input": { "model": "dev", "prompt": "Surrealist SPONGE world style humanist classical portrait,", "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: 36887\nPrompt: Surrealist SPONGE world style humanist classical portrait,\n[!] txt2img mode\nUsing dev model\nfree=8036623028224\nDownloading weights\n2024-09-05T20:23:16Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp0wa1e6sd/weights url=https://replicate.delivery/yhqm/xGJO9V4HWGawOlbbPju6wMUfTT1Y5FnDbh3TVMRrFh78P8sJA/trained_model.tar\n2024-09-05T20:23:19Z | INFO | [ Complete ] dest=/tmp/tmp0wa1e6sd/weights size=\"172 MB\" total_elapsed=3.216s url=https://replicate.delivery/yhqm/xGJO9V4HWGawOlbbPju6wMUfTT1Y5FnDbh3TVMRrFh78P8sJA/trained_model.tar\nDownloaded weights in 3.25s\nLoaded LoRAs in 11.63s\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<00:07, 3.59it/s]\n 11%|█ | 3/28 [00:00<00:07, 3.54it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.51it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.50it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.49it/s]\n 25%|██▌ | 7/28 [00:02<00:06, 3.48it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.48it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.48it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.48it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.48it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.48it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.48it/s]\n 50%|█████ | 14/28 [00:04<00:04, 3.48it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.48it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.47it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.47it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.47it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.47it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.48it/s]\n 75%|███████▌ | 21/28 [00:06<00:02, 3.48it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.48it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.47it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.47it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.47it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.47it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.47it/s]\n100%|██████████| 28/28 [00:08<00:00, 3.47it/s]\n100%|██████████| 28/28 [00:08<00:00, 3.47it/s]", "metrics": { "predict_time": 20.983513843, "total_time": 73.501491 }, "output": [ "https://replicate.delivery/yhqm/JulgOOxHmH6NG1BqnoJs3uvTE6BTs3MGEchyNnZWmPaSFfsJA/out-0.webp" ], "started_at": "2024-09-05T20:23:16.533978Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/x3r91chr21rm00chrfd9jhje3r", "cancel": "https://api.replicate.com/v1/predictions/x3r91chr21rm00chrfd9jhje3r/cancel" }, "version": "d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550" }Generated inUsing seed: 36887 Prompt: Surrealist SPONGE world style humanist classical portrait, [!] txt2img mode Using dev model free=8036623028224 Downloading weights 2024-09-05T20:23:16Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp0wa1e6sd/weights url=https://replicate.delivery/yhqm/xGJO9V4HWGawOlbbPju6wMUfTT1Y5FnDbh3TVMRrFh78P8sJA/trained_model.tar 2024-09-05T20:23:19Z | INFO | [ Complete ] dest=/tmp/tmp0wa1e6sd/weights size="172 MB" total_elapsed=3.216s url=https://replicate.delivery/yhqm/xGJO9V4HWGawOlbbPju6wMUfTT1Y5FnDbh3TVMRrFh78P8sJA/trained_model.tar Downloaded weights in 3.25s Loaded LoRAs in 11.63s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.89it/s] 7%|▋ | 2/28 [00:00<00:07, 3.59it/s] 11%|█ | 3/28 [00:00<00:07, 3.54it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.51it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.50it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.49it/s] 25%|██▌ | 7/28 [00:02<00:06, 3.48it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.48it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.48it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.48it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.48it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.48it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.48it/s] 50%|█████ | 14/28 [00:04<00:04, 3.48it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.48it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.47it/s] 61%|██████ | 17/28 [00:04<00:03, 3.47it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.47it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.47it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.48it/s] 75%|███████▌ | 21/28 [00:06<00:02, 3.48it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.48it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.47it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.47it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.47it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.47it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.47it/s] 100%|██████████| 28/28 [00:08<00:00, 3.47it/s] 100%|██████████| 28/28 [00:08<00:00, 3.47it/s]Prediction
prestoncreed/flux-spongebob:d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550IDq33r8cqrjsrm20chrfk97zcm1gStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Aurora Borealis in the SPONGE world, over a SPONGE style field
- 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": "Aurora Borealis in the SPONGE world, over a SPONGE style field ", "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 replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run prestoncreed/flux-spongebob using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "prestoncreed/flux-spongebob:d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550", { input: { model: "dev", prompt: "Aurora Borealis in the SPONGE world, over a SPONGE style field ", 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 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun prestoncreed/flux-spongebob using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "prestoncreed/flux-spongebob:d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550", input={ "model": "dev", "prompt": "Aurora Borealis in the SPONGE world, over a SPONGE style field ", "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 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run prestoncreed/flux-spongebob 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": "prestoncreed/flux-spongebob:d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550", "input": { "model": "dev", "prompt": "Aurora Borealis in the SPONGE world, over a SPONGE style field ", "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": "2024-09-05T20:37:41.196199Z", "created_at": "2024-09-05T20:36:19.734000Z", "data_removed": false, "error": null, "id": "q33r8cqrjsrm20chrfk97zcm1g", "input": { "model": "dev", "prompt": "Aurora Borealis in the SPONGE world, over a SPONGE style field ", "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: 44029\nPrompt: Aurora Borealis in the SPONGE world, over a SPONGE style field\n[!] txt2img mode\nUsing dev model\nfree=8523270168576\nDownloading weights\n2024-09-05T20:37:19Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpmzh8l9qg/weights url=https://replicate.delivery/yhqm/xGJO9V4HWGawOlbbPju6wMUfTT1Y5FnDbh3TVMRrFh78P8sJA/trained_model.tar\n2024-09-05T20:37:22Z | INFO | [ Complete ] dest=/tmp/tmpmzh8l9qg/weights size=\"172 MB\" total_elapsed=3.478s url=https://replicate.delivery/yhqm/xGJO9V4HWGawOlbbPju6wMUfTT1Y5FnDbh3TVMRrFh78P8sJA/trained_model.tar\nDownloaded weights in 3.51s\nLoaded LoRAs in 13.66s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.50it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.96it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.73it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.64it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.58it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.55it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.53it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.52it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.51it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.50it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.50it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.49it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.49it/s]\n 50%|█████ | 14/28 [00:03<00:04, 3.49it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.48it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.48it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.48it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.48it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.48it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.48it/s]\n 75%|███████▌ | 21/28 [00:05<00:02, 3.48it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.48it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.48it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.48it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.48it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.48it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.48it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.48it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.51it/s]", "metrics": { "predict_time": 22.187056212, "total_time": 81.462199 }, "output": [ "https://replicate.delivery/yhqm/MGeNLuOTERUzH6hCCO2es6fQ0RLvCm79eVLZNpcBgMMUJynNB/out-0.webp" ], "started_at": "2024-09-05T20:37:19.009143Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/q33r8cqrjsrm20chrfk97zcm1g", "cancel": "https://api.replicate.com/v1/predictions/q33r8cqrjsrm20chrfk97zcm1g/cancel" }, "version": "d82b178da97e64495663ddc21461a4a20b05109187f33d358f9b06fe79af6550" }Generated inUsing seed: 44029 Prompt: Aurora Borealis in the SPONGE world, over a SPONGE style field [!] txt2img mode Using dev model free=8523270168576 Downloading weights 2024-09-05T20:37:19Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpmzh8l9qg/weights url=https://replicate.delivery/yhqm/xGJO9V4HWGawOlbbPju6wMUfTT1Y5FnDbh3TVMRrFh78P8sJA/trained_model.tar 2024-09-05T20:37:22Z | INFO | [ Complete ] dest=/tmp/tmpmzh8l9qg/weights size="172 MB" total_elapsed=3.478s url=https://replicate.delivery/yhqm/xGJO9V4HWGawOlbbPju6wMUfTT1Y5FnDbh3TVMRrFh78P8sJA/trained_model.tar Downloaded weights in 3.51s Loaded LoRAs in 13.66s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.50it/s] 7%|▋ | 2/28 [00:00<00:06, 3.96it/s] 11%|█ | 3/28 [00:00<00:06, 3.73it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.64it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.58it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.55it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.53it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.52it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.51it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.50it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.50it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.49it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.49it/s] 50%|█████ | 14/28 [00:03<00:04, 3.49it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.48it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.48it/s] 61%|██████ | 17/28 [00:04<00:03, 3.48it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.48it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.48it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.48it/s] 75%|███████▌ | 21/28 [00:05<00:02, 3.48it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.48it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.48it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.48it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.48it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.48it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.48it/s] 100%|██████████| 28/28 [00:07<00:00, 3.48it/s] 100%|██████████| 28/28 [00:07<00:00, 3.51it/s]
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