digitaljohn
/
urban-narrative
- Public
- 136 runs
-
H100
Prediction
digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84IDnxvta60vh1rm60chhgmtm1x9w8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- an illustration of a man in new york in the style of URBNAR
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "an illustration of a man in new york in the style of URBNAR", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run digitaljohn/urban-narrative using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", { input: { model: "dev", prompt: "an illustration of a man in new york in the style of URBNAR", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "png", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, 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 digitaljohn/urban-narrative using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", input={ "model": "dev", "prompt": "an illustration of a man in new york in the style of URBNAR", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run digitaljohn/urban-narrative 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": "ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", "input": { "model": "dev", "prompt": "an illustration of a man in new york in the style of URBNAR", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "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": "2024-08-26T00:50:12.147066Z", "created_at": "2024-08-26T00:49:49.960000Z", "data_removed": false, "error": null, "id": "nxvta60vh1rm60chhgmtm1x9w8", "input": { "model": "dev", "prompt": "an illustration of a man in new york in the style of URBNAR", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 43450\nPrompt: an illustration of a man in new york in the style of URBNAR\ntxt2img mode\nUsing dev model\nfree=9637664727040\nDownloading weights\n2024-08-26T00:49:53Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpfy9fc0xx/weights url=https://replicate.delivery/yhqm/qCpCedcUjuQHGKZeJfR4h5GOluMJvvwancHrksrtVsh6zvsmA/trained_model.tar\n2024-08-26T00:49:56Z | INFO | [ Complete ] dest=/tmp/tmpfy9fc0xx/weights size=\"172 MB\" total_elapsed=3.082s url=https://replicate.delivery/yhqm/qCpCedcUjuQHGKZeJfR4h5GOluMJvvwancHrksrtVsh6zvsmA/trained_model.tar\nDownloaded weights in 3.11s\nLoaded LoRAs in 10.33s\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, 3.75it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.72it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.70it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.68it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.67it/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, 3.65it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.65it/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, 3.65it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.65it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.65it/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, 3.65it/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, 3.68it/s]", "metrics": { "predict_time": 18.726778651, "total_time": 22.187066 }, "output": [ "https://replicate.delivery/yhqm/VOPGgRsLxBaqIRpzHsCUYQudxvZ2QbJwR4vcy1rTbI1QDm1E/out-0.png" ], "started_at": "2024-08-26T00:49:53.420287Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/nxvta60vh1rm60chhgmtm1x9w8", "cancel": "https://api.replicate.com/v1/predictions/nxvta60vh1rm60chhgmtm1x9w8/cancel" }, "version": "ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84" }Generated inUsing seed: 43450 Prompt: an illustration of a man in new york in the style of URBNAR txt2img mode Using dev model free=9637664727040 Downloading weights 2024-08-26T00:49:53Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpfy9fc0xx/weights url=https://replicate.delivery/yhqm/qCpCedcUjuQHGKZeJfR4h5GOluMJvvwancHrksrtVsh6zvsmA/trained_model.tar 2024-08-26T00:49:56Z | INFO | [ Complete ] dest=/tmp/tmpfy9fc0xx/weights size="172 MB" total_elapsed=3.082s url=https://replicate.delivery/yhqm/qCpCedcUjuQHGKZeJfR4h5GOluMJvvwancHrksrtVsh6zvsmA/trained_model.tar Downloaded weights in 3.11s Loaded LoRAs in 10.33s 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, 3.75it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.72it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.70it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.68it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.67it/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, 3.65it/s] 61%|██████ | 17/28 [00:04<00:03, 3.65it/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, 3.65it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.65it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.65it/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, 3.65it/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, 3.68it/s]Prediction
digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84IDjsb0n1wpanrm60chhh0adqhh9gStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- schnell
- width
- 1024
- height
- 1024
- prompt
- an illustration of a woman looking at iphone on a london underground tube
- lora_scale
- 1.2
- num_outputs
- 1
- aspect_ratio
- 4:5
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 6
{ "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a woman looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run digitaljohn/urban-narrative using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", { input: { model: "schnell", width: 1024, height: 1024, prompt: "an illustration of a woman looking at iphone on a london underground tube", lora_scale: 1.2, num_outputs: 1, aspect_ratio: "4:5", output_format: "png", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 6 } } ); // 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 digitaljohn/urban-narrative using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", input={ "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a woman looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run digitaljohn/urban-narrative 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": "ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", "input": { "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a woman looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T01:15:30.810353Z", "created_at": "2024-08-26T01:15:28.725000Z", "data_removed": false, "error": null, "id": "jsb0n1wpanrm60chhh0adqhh9g", "input": { "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a woman looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 40080\nPrompt: an illustration of a woman looking at iphone on a london underground tube\ntxt2img mode\nUsing schnell model\nWeights already loaded\nLoaded LoRAs in 0.05s\n 0%| | 0/6 [00:00<?, ?it/s]\n 17%|█▋ | 1/6 [00:00<00:01, 4.00it/s]\n 33%|███▎ | 2/6 [00:00<00:00, 4.36it/s]\n 50%|█████ | 3/6 [00:00<00:00, 4.28it/s]\n 67%|██████▋ | 4/6 [00:00<00:00, 4.25it/s]\n 83%|████████▎ | 5/6 [00:01<00:00, 4.24it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.21it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.23it/s]", "metrics": { "predict_time": 2.078861823, "total_time": 2.085353 }, "output": [ "https://replicate.delivery/yhqm/84ebKEYtbSwMbiLQxivYb9JfcL201VPECkNJU1UIEDVykYWTA/out-0.png" ], "started_at": "2024-08-26T01:15:28.731492Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/jsb0n1wpanrm60chhh0adqhh9g", "cancel": "https://api.replicate.com/v1/predictions/jsb0n1wpanrm60chhh0adqhh9g/cancel" }, "version": "ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84" }Generated inUsing seed: 40080 Prompt: an illustration of a woman looking at iphone on a london underground tube txt2img mode Using schnell model Weights already loaded Loaded LoRAs in 0.05s 0%| | 0/6 [00:00<?, ?it/s] 17%|█▋ | 1/6 [00:00<00:01, 4.00it/s] 33%|███▎ | 2/6 [00:00<00:00, 4.36it/s] 50%|█████ | 3/6 [00:00<00:00, 4.28it/s] 67%|██████▋ | 4/6 [00:00<00:00, 4.25it/s] 83%|████████▎ | 5/6 [00:01<00:00, 4.24it/s] 100%|██████████| 6/6 [00:01<00:00, 4.21it/s] 100%|██████████| 6/6 [00:01<00:00, 4.23it/s]Prediction
digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84IDhwav9e8nddrm40chhh0vv7dnz4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- schnell
- width
- 1024
- height
- 1024
- prompt
- an illustration of a man looking at iphone on a london underground tube
- lora_scale
- 1.2
- num_outputs
- 1
- aspect_ratio
- 4:5
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 6
{ "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a man looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run digitaljohn/urban-narrative using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", { input: { model: "schnell", width: 1024, height: 1024, prompt: "an illustration of a man looking at iphone on a london underground tube", lora_scale: 1.2, num_outputs: 1, aspect_ratio: "4:5", output_format: "png", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 6 } } ); // 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 digitaljohn/urban-narrative using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", input={ "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a man looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run digitaljohn/urban-narrative 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": "ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", "input": { "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a man looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T01:16:12.147177Z", "created_at": "2024-08-26T01:16:01.259000Z", "data_removed": false, "error": null, "id": "hwav9e8nddrm40chhh0vv7dnz4", "input": { "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a man looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 37732\nPrompt: an illustration of a man looking at iphone on a london underground tube\ntxt2img mode\nUsing schnell model\nLoaded LoRAs in 8.81s\n 0%| | 0/6 [00:00<?, ?it/s]\n 17%|█▋ | 1/6 [00:00<00:01, 4.03it/s]\n 33%|███▎ | 2/6 [00:00<00:00, 4.46it/s]\n 50%|█████ | 3/6 [00:00<00:00, 4.35it/s]\n 67%|██████▋ | 4/6 [00:00<00:00, 4.30it/s]\n 83%|████████▎ | 5/6 [00:01<00:00, 4.27it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.25it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.27it/s]", "metrics": { "predict_time": 10.877751312000001, "total_time": 10.888177 }, "output": [ "https://replicate.delivery/yhqm/pl4gDsLWz5JnJ5PboP0tv3ganJsIQYAExOQq4XDw7k3WJm1E/out-0.png" ], "started_at": "2024-08-26T01:16:01.269426Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/hwav9e8nddrm40chhh0vv7dnz4", "cancel": "https://api.replicate.com/v1/predictions/hwav9e8nddrm40chhh0vv7dnz4/cancel" }, "version": "ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84" }Generated inUsing seed: 37732 Prompt: an illustration of a man looking at iphone on a london underground tube txt2img mode Using schnell model Loaded LoRAs in 8.81s 0%| | 0/6 [00:00<?, ?it/s] 17%|█▋ | 1/6 [00:00<00:01, 4.03it/s] 33%|███▎ | 2/6 [00:00<00:00, 4.46it/s] 50%|█████ | 3/6 [00:00<00:00, 4.35it/s] 67%|██████▋ | 4/6 [00:00<00:00, 4.30it/s] 83%|████████▎ | 5/6 [00:01<00:00, 4.27it/s] 100%|██████████| 6/6 [00:01<00:00, 4.25it/s] 100%|██████████| 6/6 [00:01<00:00, 4.27it/s]Prediction
digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84IDz5drvgzcj5rm00chhh0tcg79v8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- schnell
- width
- 1024
- height
- 1024
- prompt
- an illustration of a couple looking at iphone on a london underground tube
- lora_scale
- 1.2
- num_outputs
- 1
- aspect_ratio
- 4:5
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 6
{ "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a couple looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run digitaljohn/urban-narrative using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", { input: { model: "schnell", width: 1024, height: 1024, prompt: "an illustration of a couple looking at iphone on a london underground tube", lora_scale: 1.2, num_outputs: 1, aspect_ratio: "4:5", output_format: "png", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 6 } } ); // 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 digitaljohn/urban-narrative using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", input={ "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a couple looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run digitaljohn/urban-narrative 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": "ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", "input": { "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a couple looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T01:16:58.614447Z", "created_at": "2024-08-26T01:16:56.337000Z", "data_removed": false, "error": null, "id": "z5drvgzcj5rm00chhh0tcg79v8", "input": { "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a couple looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 21201\nPrompt: an illustration of a couple looking at iphone on a london underground tube\ntxt2img mode\nUsing schnell model\nWeights already loaded\nLoaded LoRAs in 0.04s\n 0%| | 0/6 [00:00<?, ?it/s]\n 17%|█▋ | 1/6 [00:00<00:01, 4.04it/s]\n 33%|███▎ | 2/6 [00:00<00:00, 4.45it/s]\n 50%|█████ | 3/6 [00:00<00:00, 4.33it/s]\n 67%|██████▋ | 4/6 [00:00<00:00, 4.28it/s]\n 83%|████████▎ | 5/6 [00:01<00:00, 4.25it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.24it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.26it/s]", "metrics": { "predict_time": 2.267519773, "total_time": 2.277447 }, "output": [ "https://replicate.delivery/yhqm/0bqZDq1MheyXWiLmmWO75fMCAssov1lgbNdjOGQaBmmKmYWTA/out-0.png" ], "started_at": "2024-08-26T01:16:56.346927Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/z5drvgzcj5rm00chhh0tcg79v8", "cancel": "https://api.replicate.com/v1/predictions/z5drvgzcj5rm00chhh0tcg79v8/cancel" }, "version": "ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84" }Generated inUsing seed: 21201 Prompt: an illustration of a couple looking at iphone on a london underground tube txt2img mode Using schnell model Weights already loaded Loaded LoRAs in 0.04s 0%| | 0/6 [00:00<?, ?it/s] 17%|█▋ | 1/6 [00:00<00:01, 4.04it/s] 33%|███▎ | 2/6 [00:00<00:00, 4.45it/s] 50%|█████ | 3/6 [00:00<00:00, 4.33it/s] 67%|██████▋ | 4/6 [00:00<00:00, 4.28it/s] 83%|████████▎ | 5/6 [00:01<00:00, 4.25it/s] 100%|██████████| 6/6 [00:01<00:00, 4.24it/s] 100%|██████████| 6/6 [00:01<00:00, 4.26it/s]Prediction
digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84IDgtkd48gsmsrm60chhh187s98r0StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- schnell
- width
- 1024
- height
- 1024
- prompt
- an illustration of a couple looking at iphone on a london underground tube
- lora_scale
- 1.2
- num_outputs
- 1
- aspect_ratio
- 4:5
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 6
{ "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a couple looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run digitaljohn/urban-narrative using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", { input: { model: "schnell", width: 1024, height: 1024, prompt: "an illustration of a couple looking at iphone on a london underground tube", lora_scale: 1.2, num_outputs: 1, aspect_ratio: "4:5", output_format: "png", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 6 } } ); // 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 digitaljohn/urban-narrative using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", input={ "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a couple looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run digitaljohn/urban-narrative 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": "ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", "input": { "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a couple looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T01:17:10.212571Z", "created_at": "2024-08-26T01:17:07.878000Z", "data_removed": false, "error": null, "id": "gtkd48gsmsrm60chhh187s98r0", "input": { "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a couple looking at iphone on a london underground tube", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 2325\nPrompt: an illustration of a couple looking at iphone on a london underground tube\ntxt2img mode\nUsing schnell model\nWeights already loaded\nLoaded LoRAs in 0.05s\n 0%| | 0/6 [00:00<?, ?it/s]\n 17%|█▋ | 1/6 [00:00<00:01, 4.01it/s]\n 33%|███▎ | 2/6 [00:00<00:00, 4.39it/s]\n 50%|█████ | 3/6 [00:00<00:00, 4.30it/s]\n 67%|██████▋ | 4/6 [00:00<00:00, 4.26it/s]\n 83%|████████▎ | 5/6 [00:01<00:00, 4.24it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.24it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.25it/s]", "metrics": { "predict_time": 2.324330277, "total_time": 2.334571 }, "output": [ "https://replicate.delivery/yhqm/t7dq4L4Ppva6Ad4cqt9fMwwZkn6PD9yZVBXlc7MbLvOLTMrJA/out-0.png" ], "started_at": "2024-08-26T01:17:07.888240Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/gtkd48gsmsrm60chhh187s98r0", "cancel": "https://api.replicate.com/v1/predictions/gtkd48gsmsrm60chhh187s98r0/cancel" }, "version": "ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84" }Generated inUsing seed: 2325 Prompt: an illustration of a couple looking at iphone on a london underground tube txt2img mode Using schnell model Weights already loaded Loaded LoRAs in 0.05s 0%| | 0/6 [00:00<?, ?it/s] 17%|█▋ | 1/6 [00:00<00:01, 4.01it/s] 33%|███▎ | 2/6 [00:00<00:00, 4.39it/s] 50%|█████ | 3/6 [00:00<00:00, 4.30it/s] 67%|██████▋ | 4/6 [00:00<00:00, 4.26it/s] 83%|████████▎ | 5/6 [00:01<00:00, 4.24it/s] 100%|██████████| 6/6 [00:01<00:00, 4.24it/s] 100%|██████████| 6/6 [00:01<00:00, 4.25it/s]Prediction
digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84IDvf97ez65pnrm00chhh1ayfnr0cStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- schnell
- width
- 1024
- height
- 1024
- prompt
- an illustration of a couple looking at iphone on a london underground tube. text says "LONDON PADDINGTON"
- lora_scale
- 1.2
- num_outputs
- 1
- aspect_ratio
- 4:5
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 6
{ "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a couple looking at iphone on a london underground tube. text says \"LONDON PADDINGTON\"", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run digitaljohn/urban-narrative using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", { input: { model: "schnell", width: 1024, height: 1024, prompt: "an illustration of a couple looking at iphone on a london underground tube. text says \"LONDON PADDINGTON\"", lora_scale: 1.2, num_outputs: 1, aspect_ratio: "4:5", output_format: "png", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 6 } } ); // 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 digitaljohn/urban-narrative using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "digitaljohn/urban-narrative:ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", input={ "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a couple looking at iphone on a london underground tube. text says \"LONDON PADDINGTON\"", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run digitaljohn/urban-narrative 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": "ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84", "input": { "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a couple looking at iphone on a london underground tube. text says \\"LONDON PADDINGTON\\"", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T01:17:54.099502Z", "created_at": "2024-08-26T01:17:51.925000Z", "data_removed": false, "error": null, "id": "vf97ez65pnrm00chhh1ayfnr0c", "input": { "model": "schnell", "width": 1024, "height": 1024, "prompt": "an illustration of a couple looking at iphone on a london underground tube. text says \"LONDON PADDINGTON\"", "lora_scale": 1.2, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 4259\nPrompt: an illustration of a couple looking at iphone on a london underground tube. text says \"LONDON PADDINGTON\"\ntxt2img mode\nUsing schnell model\nWeights already loaded\nLoaded LoRAs in 0.04s\n 0%| | 0/6 [00:00<?, ?it/s]\n 17%|█▋ | 1/6 [00:00<00:01, 4.03it/s]\n 33%|███▎ | 2/6 [00:00<00:00, 4.45it/s]\n 50%|█████ | 3/6 [00:00<00:00, 4.34it/s]\n 67%|██████▋ | 4/6 [00:00<00:00, 4.28it/s]\n 83%|████████▎ | 5/6 [00:01<00:00, 4.26it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.24it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.27it/s]", "metrics": { "predict_time": 2.163734393, "total_time": 2.174502 }, "output": [ "https://replicate.delivery/yhqm/9l2iorXTie3IQKcf5r2daL8OoGzE5TkyyviOtHpS0LJBnYWTA/out-0.png" ], "started_at": "2024-08-26T01:17:51.935767Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vf97ez65pnrm00chhh1ayfnr0c", "cancel": "https://api.replicate.com/v1/predictions/vf97ez65pnrm00chhh1ayfnr0c/cancel" }, "version": "ea830af4eeb1f0c3d9eb209ecbbc4ef14bcb8d51ac59b6d0a8dc2eb632a2fa84" }Generated inUsing seed: 4259 Prompt: an illustration of a couple looking at iphone on a london underground tube. text says "LONDON PADDINGTON" txt2img mode Using schnell model Weights already loaded Loaded LoRAs in 0.04s 0%| | 0/6 [00:00<?, ?it/s] 17%|█▋ | 1/6 [00:00<00:01, 4.03it/s] 33%|███▎ | 2/6 [00:00<00:00, 4.45it/s] 50%|█████ | 3/6 [00:00<00:00, 4.34it/s] 67%|██████▋ | 4/6 [00:00<00:00, 4.28it/s] 83%|████████▎ | 5/6 [00:01<00:00, 4.26it/s] 100%|██████████| 6/6 [00:01<00:00, 4.24it/s] 100%|██████████| 6/6 [00:01<00:00, 4.27it/s]
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