adirik / flux-fantasy-architecture
Flux lora, use "in the style of FNTSYRCH" to trigger
- Public
- 1.2K runs
-
H100
Prediction
adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333IDgvwy1z4qwnrm20chg318pvqp7gStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- An oriental urban landscape, in the style of FNTSYRCH
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "An oriental urban landscape, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 adirik/flux-fantasy-architecture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", { input: { model: "dev", prompt: "An oriental urban landscape, in the style of FNTSYRCH", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 adirik/flux-fantasy-architecture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", input={ "model": "dev", "prompt": "An oriental urban landscape, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run adirik/flux-fantasy-architecture 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": "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", "input": { "model": "dev", "prompt": "An oriental urban landscape, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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": "2024-08-23T19:42:20.759148Z", "created_at": "2024-08-23T19:42:02.213000Z", "data_removed": false, "error": null, "id": "gvwy1z4qwnrm20chg318pvqp7g", "input": { "model": "dev", "prompt": "An oriental urban landscape, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 42333\nPrompt: An oriental urban landscape, in the style of FNTSYRCH\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9556055891968\nDownloading weights\n2024-08-23T19:42:02Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/d1adb9419b77ae1d url=https://replicate.delivery/yhqm/dpAdaUmDUIKmJV6BXQoK07Lk7XHUHP9rBQ5pHGvYgu4HXa1E/trained_model.tar\n2024-08-23T19:42:04Z | INFO | [ Complete ] dest=/src/weights-cache/d1adb9419b77ae1d size=\"172 MB\" total_elapsed=1.757s url=https://replicate.delivery/yhqm/dpAdaUmDUIKmJV6BXQoK07Lk7XHUHP9rBQ5pHGvYgu4HXa1E/trained_model.tar\nb''\nDownloaded weights in 1.783931016921997 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.69it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.26it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.99it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.77it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.75it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.71it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.71it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.70it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.70it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.70it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.70it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.73it/s]", "metrics": { "predict_time": 18.533449275, "total_time": 18.546148 }, "output": [ "https://replicate.delivery/yhqm/jBLXNg09IeyLRyFCeEuxC6glY2GFT1Fn1NQYc0VGEve5ATrmA/out-0.webp" ], "started_at": "2024-08-23T19:42:02.225698Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/gvwy1z4qwnrm20chg318pvqp7g", "cancel": "https://api.replicate.com/v1/predictions/gvwy1z4qwnrm20chg318pvqp7g/cancel" }, "version": "8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333" }Generated inUsing seed: 42333 Prompt: An oriental urban landscape, in the style of FNTSYRCH txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9556055891968 Downloading weights 2024-08-23T19:42:02Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/d1adb9419b77ae1d url=https://replicate.delivery/yhqm/dpAdaUmDUIKmJV6BXQoK07Lk7XHUHP9rBQ5pHGvYgu4HXa1E/trained_model.tar 2024-08-23T19:42:04Z | INFO | [ Complete ] dest=/src/weights-cache/d1adb9419b77ae1d size="172 MB" total_elapsed=1.757s url=https://replicate.delivery/yhqm/dpAdaUmDUIKmJV6BXQoK07Lk7XHUHP9rBQ5pHGvYgu4HXa1E/trained_model.tar b'' Downloaded weights in 1.783931016921997 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.69it/s] 7%|▋ | 2/28 [00:00<00:06, 4.26it/s] 11%|█ | 3/28 [00:00<00:06, 3.99it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.77it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.75it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.71it/s] 50%|█████ | 14/28 [00:03<00:03, 3.71it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s] 61%|██████ | 17/28 [00:04<00:02, 3.70it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.70it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.70it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.70it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.73it/s]Prediction
adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333IDcv794ht79srm20chg32a9d3dtmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- A drawing of a skyscraper with classical elements, in the style of FNTSYRCH
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "A drawing of a skyscraper with classical elements, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 adirik/flux-fantasy-architecture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", { input: { model: "dev", prompt: "A drawing of a skyscraper with classical elements, in the style of FNTSYRCH", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 adirik/flux-fantasy-architecture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", input={ "model": "dev", "prompt": "A drawing of a skyscraper with classical elements, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run adirik/flux-fantasy-architecture 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": "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", "input": { "model": "dev", "prompt": "A drawing of a skyscraper with classical elements, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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": "2024-08-23T19:44:12.904022Z", "created_at": "2024-08-23T19:43:52.654000Z", "data_removed": false, "error": null, "id": "cv794ht79srm20chg32a9d3dtm", "input": { "model": "dev", "prompt": "A drawing of a skyscraper with classical elements, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 38058\nPrompt: A drawing of a skyscraper with classical elements, in the style of FNTSYRCH\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9414433087488\nDownloading weights\n2024-08-23T19:43:53Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/d1adb9419b77ae1d url=https://replicate.delivery/yhqm/dpAdaUmDUIKmJV6BXQoK07Lk7XHUHP9rBQ5pHGvYgu4HXa1E/trained_model.tar\n2024-08-23T19:43:55Z | INFO | [ Complete ] dest=/src/weights-cache/d1adb9419b77ae1d size=\"172 MB\" total_elapsed=1.916s url=https://replicate.delivery/yhqm/dpAdaUmDUIKmJV6BXQoK07Lk7XHUHP9rBQ5pHGvYgu4HXa1E/trained_model.tar\nb''\nDownloaded weights in 1.943753719329834 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.69it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.25it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.97it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.79it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.72it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.68it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.68it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.71it/s]", "metrics": { "predict_time": 19.424181582, "total_time": 20.250022 }, "output": [ "https://replicate.delivery/yhqm/cVqFLuvEzCqjJ9lGgfttbG9aQ7pzaka1hKfUL4bZ5AWMipVTA/out-0.webp" ], "started_at": "2024-08-23T19:43:53.479840Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/cv794ht79srm20chg32a9d3dtm", "cancel": "https://api.replicate.com/v1/predictions/cv794ht79srm20chg32a9d3dtm/cancel" }, "version": "8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333" }Generated inUsing seed: 38058 Prompt: A drawing of a skyscraper with classical elements, in the style of FNTSYRCH txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9414433087488 Downloading weights 2024-08-23T19:43:53Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/d1adb9419b77ae1d url=https://replicate.delivery/yhqm/dpAdaUmDUIKmJV6BXQoK07Lk7XHUHP9rBQ5pHGvYgu4HXa1E/trained_model.tar 2024-08-23T19:43:55Z | INFO | [ Complete ] dest=/src/weights-cache/d1adb9419b77ae1d size="172 MB" total_elapsed=1.916s url=https://replicate.delivery/yhqm/dpAdaUmDUIKmJV6BXQoK07Lk7XHUHP9rBQ5pHGvYgu4HXa1E/trained_model.tar b'' Downloaded weights in 1.943753719329834 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.69it/s] 7%|▋ | 2/28 [00:00<00:06, 4.25it/s] 11%|█ | 3/28 [00:00<00:06, 3.97it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.79it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.72it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s] 50%|█████ | 14/28 [00:03<00:03, 3.68it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s] 61%|██████ | 17/28 [00:04<00:02, 3.68it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s] 100%|██████████| 28/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.71it/s]Prediction
adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333ID0maqk5n559rm60chg34bcy1k60StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Drawing of a public park with two ponds and a running track, in the style of FNTSYRCH
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "Drawing of a public park with two ponds and a running track, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 adirik/flux-fantasy-architecture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", { input: { model: "dev", prompt: "Drawing of a public park with two ponds and a running track, in the style of FNTSYRCH", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 adirik/flux-fantasy-architecture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", input={ "model": "dev", "prompt": "Drawing of a public park with two ponds and a running track, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run adirik/flux-fantasy-architecture 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": "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", "input": { "model": "dev", "prompt": "Drawing of a public park with two ponds and a running track, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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": "2024-08-23T19:49:05.154225Z", "created_at": "2024-08-23T19:48:38.826000Z", "data_removed": false, "error": null, "id": "0maqk5n559rm60chg34bcy1k60", "input": { "model": "dev", "prompt": "Drawing of a public park with two ponds and a running track, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 47766\nPrompt: Drawing of a public park with two ponds and a running track, in the style of FNTSYRCH\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.67it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.97it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.79it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.71it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.69it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.69it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.69it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.68it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.71it/s]", "metrics": { "predict_time": 17.701955911, "total_time": 26.328225 }, "output": [ "https://replicate.delivery/yhqm/cwdG81rOeBx4HqgRiD5imiiEaa21nhyGmOJbRlRiYdQYz0qJA/out-0.webp" ], "started_at": "2024-08-23T19:48:47.452269Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/0maqk5n559rm60chg34bcy1k60", "cancel": "https://api.replicate.com/v1/predictions/0maqk5n559rm60chg34bcy1k60/cancel" }, "version": "8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333" }Generated inUsing seed: 47766 Prompt: Drawing of a public park with two ponds and a running track, in the style of FNTSYRCH txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.67it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.97it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.79it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.71it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.69it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s] 50%|█████ | 14/28 [00:03<00:03, 3.69it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.69it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s] 61%|██████ | 17/28 [00:04<00:02, 3.68it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s] 100%|██████████| 28/28 [00:07<00:00, 3.68it/s] 100%|██████████| 28/28 [00:07<00:00, 3.71it/s]Prediction
adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333ID8xyr67ya65rm00chg34vyy1zq0StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Drawing of a space shuttle interior, in the style of FNTSYRCH
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "Drawing of a space shuttle interior, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 adirik/flux-fantasy-architecture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", { input: { model: "dev", prompt: "Drawing of a space shuttle interior, in the style of FNTSYRCH", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 adirik/flux-fantasy-architecture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", input={ "model": "dev", "prompt": "Drawing of a space shuttle interior, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run adirik/flux-fantasy-architecture 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": "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", "input": { "model": "dev", "prompt": "Drawing of a space shuttle interior, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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": "2024-08-23T19:50:12.450706Z", "created_at": "2024-08-23T19:49:53.841000Z", "data_removed": false, "error": null, "id": "8xyr67ya65rm00chg34vyy1zq0", "input": { "model": "dev", "prompt": "Drawing of a space shuttle interior, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 61215\nPrompt: Drawing of a space shuttle interior, in the style of FNTSYRCH\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.66it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.22it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.94it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.82it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.69it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.67it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.67it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.66it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.66it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.66it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.66it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.65it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.66it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.66it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.66it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.66it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.66it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]", "metrics": { "predict_time": 17.727216275, "total_time": 18.609706 }, "output": [ "https://replicate.delivery/yhqm/eNtqMpOXcYRfA05BXTUkM7ke28LWtJdnCvy5yJS4xinpPTrmA/out-0.webp" ], "started_at": "2024-08-23T19:49:54.723490Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/8xyr67ya65rm00chg34vyy1zq0", "cancel": "https://api.replicate.com/v1/predictions/8xyr67ya65rm00chg34vyy1zq0/cancel" }, "version": "8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333" }Generated inUsing seed: 61215 Prompt: Drawing of a space shuttle interior, in the style of FNTSYRCH txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.66it/s] 7%|▋ | 2/28 [00:00<00:06, 4.22it/s] 11%|█ | 3/28 [00:00<00:06, 3.94it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.82it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.69it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.67it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.67it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.66it/s] 50%|█████ | 14/28 [00:03<00:03, 3.66it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.66it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s] 61%|██████ | 17/28 [00:04<00:03, 3.66it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.65it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.66it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.66it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.66it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.66it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.66it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s]Prediction
adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333IDn44dmrd58srm60chg35b7x9nrgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Colorful illustration of a cultural centre, in the style of FNTSYRCH
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "Colorful illustration of a cultural centre, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 adirik/flux-fantasy-architecture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", { input: { model: "dev", prompt: "Colorful illustration of a cultural centre, in the style of FNTSYRCH", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 adirik/flux-fantasy-architecture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", input={ "model": "dev", "prompt": "Colorful illustration of a cultural centre, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run adirik/flux-fantasy-architecture 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": "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", "input": { "model": "dev", "prompt": "Colorful illustration of a cultural centre, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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": "2024-08-23T19:51:11.346168Z", "created_at": "2024-08-23T19:50:49.926000Z", "data_removed": false, "error": null, "id": "n44dmrd58srm60chg35b7x9nrg", "input": { "model": "dev", "prompt": "Colorful illustration of a cultural centre, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 55547\nPrompt: Colorful illustration of a cultural centre, in the style of FNTSYRCH\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.66it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.21it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.95it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.83it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.69it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.67it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.67it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.66it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.66it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.66it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.66it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.66it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.66it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.66it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.66it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.66it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.66it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.66it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.65it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]", "metrics": { "predict_time": 16.647639287, "total_time": 21.420168 }, "output": [ "https://replicate.delivery/yhqm/F1eL1aePxrpYIEDAGfeY5q6w1khk66MI9ZQfJLUa1fP6Laa1E/out-0.webp" ], "started_at": "2024-08-23T19:50:54.698529Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/n44dmrd58srm60chg35b7x9nrg", "cancel": "https://api.replicate.com/v1/predictions/n44dmrd58srm60chg35b7x9nrg/cancel" }, "version": "8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333" }Generated inUsing seed: 55547 Prompt: Colorful illustration of a cultural centre, in the style of FNTSYRCH txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.66it/s] 7%|▋ | 2/28 [00:00<00:06, 4.21it/s] 11%|█ | 3/28 [00:00<00:06, 3.95it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.83it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.69it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.67it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.67it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.66it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.66it/s] 50%|█████ | 14/28 [00:03<00:03, 3.66it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.66it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s] 61%|██████ | 17/28 [00:04<00:03, 3.66it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.66it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.66it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.66it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.66it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.66it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.66it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.65it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s]Prediction
adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333IDyzzxjjzwasrm40chg35rr8z4e4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Drawing of a suspension bridge connecting two cities, in the style of FNTSYRCH
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "Drawing of a suspension bridge connecting two cities, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 adirik/flux-fantasy-architecture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", { input: { model: "dev", prompt: "Drawing of a suspension bridge connecting two cities, in the style of FNTSYRCH", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 adirik/flux-fantasy-architecture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", input={ "model": "dev", "prompt": "Drawing of a suspension bridge connecting two cities, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run adirik/flux-fantasy-architecture 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": "adirik/flux-fantasy-architecture:8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333", "input": { "model": "dev", "prompt": "Drawing of a suspension bridge connecting two cities, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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": "2024-08-23T19:52:34.315782Z", "created_at": "2024-08-23T19:52:17.750000Z", "data_removed": false, "error": null, "id": "yzzxjjzwasrm40chg35rr8z4e4", "input": { "model": "dev", "prompt": "Drawing of a suspension bridge connecting two cities, in the style of FNTSYRCH", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 896\nPrompt: Drawing of a suspension bridge connecting two cities, in the style of FNTSYRCH\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.69it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.26it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.99it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.77it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.71it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.71it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.70it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.70it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.70it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.70it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.73it/s]", "metrics": { "predict_time": 16.55599669, "total_time": 16.565782 }, "output": [ "https://replicate.delivery/yhqm/z4FxWr6Yyt4SNpaPTVKrPcTNiQ4865yNWiRm3NAALDlgaa1E/out-0.webp" ], "started_at": "2024-08-23T19:52:17.759785Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/yzzxjjzwasrm40chg35rr8z4e4", "cancel": "https://api.replicate.com/v1/predictions/yzzxjjzwasrm40chg35rr8z4e4/cancel" }, "version": "8bd08a5e1b0eaa17d16122e86bffe9d63f0e8cf391fd47144489902975f3f333" }Generated inUsing seed: 896 Prompt: Drawing of a suspension bridge connecting two cities, in the style of FNTSYRCH txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.69it/s] 7%|▋ | 2/28 [00:00<00:06, 4.26it/s] 11%|█ | 3/28 [00:00<00:06, 3.99it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.77it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.71it/s] 50%|█████ | 14/28 [00:03<00:03, 3.71it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s] 61%|██████ | 17/28 [00:04<00:02, 3.70it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.70it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.70it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.70it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.73it/s]
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