levelsio / neon-tokyo
Take photos in the style of rainy Tokyo nights with neon lights
- Public
- 8.3K runs
-
H100
Prediction
levelsio/neon-tokyo:64d1f3c37e1702a4b659e6373b3e4b7b4d1feda75337d9581bc3e893df516436IDjcwaqczvj9rm40chq25s81jpygStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a street at night rainy in style of TKYO
- lora_scale
- 0.75
- num_outputs
- 4
- aspect_ratio
- 4:3
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a street at night rainy in style of TKYO", "lora_scale": 0.75, "num_outputs": 4, "aspect_ratio": "4:3", "output_format": "jpg", "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 levelsio/neon-tokyo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "levelsio/neon-tokyo:64d1f3c37e1702a4b659e6373b3e4b7b4d1feda75337d9581bc3e893df516436", { input: { model: "dev", prompt: "a street at night rainy in style of TKYO", lora_scale: 0.75, num_outputs: 4, aspect_ratio: "4:3", output_format: "jpg", 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 levelsio/neon-tokyo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "levelsio/neon-tokyo:64d1f3c37e1702a4b659e6373b3e4b7b4d1feda75337d9581bc3e893df516436", input={ "model": "dev", "prompt": "a street at night rainy in style of TKYO", "lora_scale": 0.75, "num_outputs": 4, "aspect_ratio": "4:3", "output_format": "jpg", "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 levelsio/neon-tokyo 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": "levelsio/neon-tokyo:64d1f3c37e1702a4b659e6373b3e4b7b4d1feda75337d9581bc3e893df516436", "input": { "model": "dev", "prompt": "a street at night rainy in style of TKYO", "lora_scale": 0.75, "num_outputs": 4, "aspect_ratio": "4:3", "output_format": "jpg", "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": "2024-09-03T15:42:55.376440Z", "created_at": "2024-09-03T15:41:07.346000Z", "data_removed": false, "error": null, "id": "jcwaqczvj9rm40chq25s81jpyg", "input": { "model": "dev", "prompt": "a street at night rainy in style of TKYO", "lora_scale": 0.75, "num_outputs": 4, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 2122\nPrompt: a street at night rainy in style of TKYO\ntxt2img mode\nUsing dev model\nfree=9021488508928\nDownloading weights\n2024-09-03T15:42:07Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpdr_romr3/weights url=https://replicate.delivery/yhqm/wcEw4wgidoaBNRtwPlbPsmE6NrOpjtJhYlqYKQsJGC26YT2E/trained_model.tar\n2024-09-03T15:42:09Z | INFO | [ Complete ] dest=/tmp/tmpdr_romr3/weights size=\"172 MB\" total_elapsed=2.100s url=https://replicate.delivery/yhqm/wcEw4wgidoaBNRtwPlbPsmE6NrOpjtJhYlqYKQsJGC26YT2E/trained_model.tar\nDownloaded weights in 2.12s\nLoaded LoRAs in 18.37s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:27, 1.01s/it]\n 7%|▋ | 2/28 [00:01<00:23, 1.12it/s]\n 11%|█ | 3/28 [00:02<00:23, 1.06it/s]\n 14%|█▍ | 4/28 [00:03<00:23, 1.03it/s]\n 18%|█▊ | 5/28 [00:04<00:22, 1.02it/s]\n 21%|██▏ | 6/28 [00:05<00:21, 1.01it/s]\n 25%|██▌ | 7/28 [00:06<00:20, 1.01it/s]\n 29%|██▊ | 8/28 [00:07<00:19, 1.00it/s]\n 32%|███▏ | 9/28 [00:08<00:19, 1.00s/it]\n 36%|███▌ | 10/28 [00:09<00:18, 1.01s/it]\n 39%|███▉ | 11/28 [00:10<00:17, 1.01s/it]\n 43%|████▎ | 12/28 [00:11<00:16, 1.01s/it]\n 46%|████▋ | 13/28 [00:12<00:15, 1.01s/it]\n 50%|█████ | 14/28 [00:13<00:14, 1.01s/it]\n 54%|█████▎ | 15/28 [00:14<00:13, 1.01s/it]\n 57%|█████▋ | 16/28 [00:15<00:12, 1.01s/it]\n 61%|██████ | 17/28 [00:16<00:11, 1.01s/it]\n 64%|██████▍ | 18/28 [00:17<00:10, 1.01s/it]\n 68%|██████▊ | 19/28 [00:18<00:09, 1.01s/it]\n 71%|███████▏ | 20/28 [00:19<00:08, 1.01s/it]\n 75%|███████▌ | 21/28 [00:20<00:07, 1.01s/it]\n 79%|███████▊ | 22/28 [00:21<00:06, 1.01s/it]\n 82%|████████▏ | 23/28 [00:23<00:05, 1.01s/it]\n 86%|████████▌ | 24/28 [00:24<00:04, 1.01s/it]\n 89%|████████▉ | 25/28 [00:25<00:03, 1.01s/it]\n 93%|█████████▎| 26/28 [00:26<00:02, 1.01s/it]\n 96%|█████████▋| 27/28 [00:27<00:01, 1.01s/it]\n100%|██████████| 28/28 [00:28<00:00, 1.01s/it]\n100%|██████████| 28/28 [00:28<00:00, 1.00s/it]", "metrics": { "predict_time": 47.777099253, "total_time": 108.03044 }, "output": [ "https://replicate.delivery/yhqm/O7xI1qB01f2CfkKZFuMNZEShRsw1LonudULn8LQHyie8DcymA/out-0.jpg", "https://replicate.delivery/yhqm/hG23GdlE645wGtJYRjEa9rM2EHT9xORUOkPnkYXc4b0fAnsJA/out-1.jpg", "https://replicate.delivery/yhqm/JLPBK911fzXkcKkwpyQZYldnhGh2Pq5j7zLTCPqRyokfBOZTA/out-2.jpg", "https://replicate.delivery/yhqm/qib0nzBVTwanLFTTaf4YRq4VjtS1tP03HfnzbjEiEdXfDcymA/out-3.jpg" ], "started_at": "2024-09-03T15:42:07.599340Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/jcwaqczvj9rm40chq25s81jpyg", "cancel": "https://api.replicate.com/v1/predictions/jcwaqczvj9rm40chq25s81jpyg/cancel" }, "version": "64d1f3c37e1702a4b659e6373b3e4b7b4d1feda75337d9581bc3e893df516436" }Generated inUsing seed: 2122 Prompt: a street at night rainy in style of TKYO txt2img mode Using dev model free=9021488508928 Downloading weights 2024-09-03T15:42:07Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpdr_romr3/weights url=https://replicate.delivery/yhqm/wcEw4wgidoaBNRtwPlbPsmE6NrOpjtJhYlqYKQsJGC26YT2E/trained_model.tar 2024-09-03T15:42:09Z | INFO | [ Complete ] dest=/tmp/tmpdr_romr3/weights size="172 MB" total_elapsed=2.100s url=https://replicate.delivery/yhqm/wcEw4wgidoaBNRtwPlbPsmE6NrOpjtJhYlqYKQsJGC26YT2E/trained_model.tar Downloaded weights in 2.12s Loaded LoRAs in 18.37s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:27, 1.01s/it] 7%|▋ | 2/28 [00:01<00:23, 1.12it/s] 11%|█ | 3/28 [00:02<00:23, 1.06it/s] 14%|█▍ | 4/28 [00:03<00:23, 1.03it/s] 18%|█▊ | 5/28 [00:04<00:22, 1.02it/s] 21%|██▏ | 6/28 [00:05<00:21, 1.01it/s] 25%|██▌ | 7/28 [00:06<00:20, 1.01it/s] 29%|██▊ | 8/28 [00:07<00:19, 1.00it/s] 32%|███▏ | 9/28 [00:08<00:19, 1.00s/it] 36%|███▌ | 10/28 [00:09<00:18, 1.01s/it] 39%|███▉ | 11/28 [00:10<00:17, 1.01s/it] 43%|████▎ | 12/28 [00:11<00:16, 1.01s/it] 46%|████▋ | 13/28 [00:12<00:15, 1.01s/it] 50%|█████ | 14/28 [00:13<00:14, 1.01s/it] 54%|█████▎ | 15/28 [00:14<00:13, 1.01s/it] 57%|█████▋ | 16/28 [00:15<00:12, 1.01s/it] 61%|██████ | 17/28 [00:16<00:11, 1.01s/it] 64%|██████▍ | 18/28 [00:17<00:10, 1.01s/it] 68%|██████▊ | 19/28 [00:18<00:09, 1.01s/it] 71%|███████▏ | 20/28 [00:19<00:08, 1.01s/it] 75%|███████▌ | 21/28 [00:20<00:07, 1.01s/it] 79%|███████▊ | 22/28 [00:21<00:06, 1.01s/it] 82%|████████▏ | 23/28 [00:23<00:05, 1.01s/it] 86%|████████▌ | 24/28 [00:24<00:04, 1.01s/it] 89%|████████▉ | 25/28 [00:25<00:03, 1.01s/it] 93%|█████████▎| 26/28 [00:26<00:02, 1.01s/it] 96%|█████████▋| 27/28 [00:27<00:01, 1.01s/it] 100%|██████████| 28/28 [00:28<00:00, 1.01s/it] 100%|██████████| 28/28 [00:28<00:00, 1.00s/it]Prediction
levelsio/neon-tokyo:64d1f3c37e1702a4b659e6373b3e4b7b4d1feda75337d9581bc3e893df516436IDjcwaqczvj9rm40chq25s81jpygStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a street at night rainy in style of TKYO
- lora_scale
- 0.75
- num_outputs
- 4
- aspect_ratio
- 4:3
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a street at night rainy in style of TKYO", "lora_scale": 0.75, "num_outputs": 4, "aspect_ratio": "4:3", "output_format": "jpg", "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 levelsio/neon-tokyo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "levelsio/neon-tokyo:64d1f3c37e1702a4b659e6373b3e4b7b4d1feda75337d9581bc3e893df516436", { input: { model: "dev", prompt: "a street at night rainy in style of TKYO", lora_scale: 0.75, num_outputs: 4, aspect_ratio: "4:3", output_format: "jpg", 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 levelsio/neon-tokyo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "levelsio/neon-tokyo:64d1f3c37e1702a4b659e6373b3e4b7b4d1feda75337d9581bc3e893df516436", input={ "model": "dev", "prompt": "a street at night rainy in style of TKYO", "lora_scale": 0.75, "num_outputs": 4, "aspect_ratio": "4:3", "output_format": "jpg", "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 levelsio/neon-tokyo 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": "levelsio/neon-tokyo:64d1f3c37e1702a4b659e6373b3e4b7b4d1feda75337d9581bc3e893df516436", "input": { "model": "dev", "prompt": "a street at night rainy in style of TKYO", "lora_scale": 0.75, "num_outputs": 4, "aspect_ratio": "4:3", "output_format": "jpg", "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": "2024-09-03T15:42:55.376440Z", "created_at": "2024-09-03T15:41:07.346000Z", "data_removed": false, "error": null, "id": "jcwaqczvj9rm40chq25s81jpyg", "input": { "model": "dev", "prompt": "a street at night rainy in style of TKYO", "lora_scale": 0.75, "num_outputs": 4, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 2122\nPrompt: a street at night rainy in style of TKYO\ntxt2img mode\nUsing dev model\nfree=9021488508928\nDownloading weights\n2024-09-03T15:42:07Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpdr_romr3/weights url=https://replicate.delivery/yhqm/wcEw4wgidoaBNRtwPlbPsmE6NrOpjtJhYlqYKQsJGC26YT2E/trained_model.tar\n2024-09-03T15:42:09Z | INFO | [ Complete ] dest=/tmp/tmpdr_romr3/weights size=\"172 MB\" total_elapsed=2.100s url=https://replicate.delivery/yhqm/wcEw4wgidoaBNRtwPlbPsmE6NrOpjtJhYlqYKQsJGC26YT2E/trained_model.tar\nDownloaded weights in 2.12s\nLoaded LoRAs in 18.37s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:27, 1.01s/it]\n 7%|▋ | 2/28 [00:01<00:23, 1.12it/s]\n 11%|█ | 3/28 [00:02<00:23, 1.06it/s]\n 14%|█▍ | 4/28 [00:03<00:23, 1.03it/s]\n 18%|█▊ | 5/28 [00:04<00:22, 1.02it/s]\n 21%|██▏ | 6/28 [00:05<00:21, 1.01it/s]\n 25%|██▌ | 7/28 [00:06<00:20, 1.01it/s]\n 29%|██▊ | 8/28 [00:07<00:19, 1.00it/s]\n 32%|███▏ | 9/28 [00:08<00:19, 1.00s/it]\n 36%|███▌ | 10/28 [00:09<00:18, 1.01s/it]\n 39%|███▉ | 11/28 [00:10<00:17, 1.01s/it]\n 43%|████▎ | 12/28 [00:11<00:16, 1.01s/it]\n 46%|████▋ | 13/28 [00:12<00:15, 1.01s/it]\n 50%|█████ | 14/28 [00:13<00:14, 1.01s/it]\n 54%|█████▎ | 15/28 [00:14<00:13, 1.01s/it]\n 57%|█████▋ | 16/28 [00:15<00:12, 1.01s/it]\n 61%|██████ | 17/28 [00:16<00:11, 1.01s/it]\n 64%|██████▍ | 18/28 [00:17<00:10, 1.01s/it]\n 68%|██████▊ | 19/28 [00:18<00:09, 1.01s/it]\n 71%|███████▏ | 20/28 [00:19<00:08, 1.01s/it]\n 75%|███████▌ | 21/28 [00:20<00:07, 1.01s/it]\n 79%|███████▊ | 22/28 [00:21<00:06, 1.01s/it]\n 82%|████████▏ | 23/28 [00:23<00:05, 1.01s/it]\n 86%|████████▌ | 24/28 [00:24<00:04, 1.01s/it]\n 89%|████████▉ | 25/28 [00:25<00:03, 1.01s/it]\n 93%|█████████▎| 26/28 [00:26<00:02, 1.01s/it]\n 96%|█████████▋| 27/28 [00:27<00:01, 1.01s/it]\n100%|██████████| 28/28 [00:28<00:00, 1.01s/it]\n100%|██████████| 28/28 [00:28<00:00, 1.00s/it]", "metrics": { "predict_time": 47.777099253, "total_time": 108.03044 }, "output": [ "https://replicate.delivery/yhqm/O7xI1qB01f2CfkKZFuMNZEShRsw1LonudULn8LQHyie8DcymA/out-0.jpg", "https://replicate.delivery/yhqm/hG23GdlE645wGtJYRjEa9rM2EHT9xORUOkPnkYXc4b0fAnsJA/out-1.jpg", "https://replicate.delivery/yhqm/JLPBK911fzXkcKkwpyQZYldnhGh2Pq5j7zLTCPqRyokfBOZTA/out-2.jpg", "https://replicate.delivery/yhqm/qib0nzBVTwanLFTTaf4YRq4VjtS1tP03HfnzbjEiEdXfDcymA/out-3.jpg" ], "started_at": "2024-09-03T15:42:07.599340Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/jcwaqczvj9rm40chq25s81jpyg", "cancel": "https://api.replicate.com/v1/predictions/jcwaqczvj9rm40chq25s81jpyg/cancel" }, "version": "64d1f3c37e1702a4b659e6373b3e4b7b4d1feda75337d9581bc3e893df516436" }Generated inUsing seed: 2122 Prompt: a street at night rainy in style of TKYO txt2img mode Using dev model free=9021488508928 Downloading weights 2024-09-03T15:42:07Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpdr_romr3/weights url=https://replicate.delivery/yhqm/wcEw4wgidoaBNRtwPlbPsmE6NrOpjtJhYlqYKQsJGC26YT2E/trained_model.tar 2024-09-03T15:42:09Z | INFO | [ Complete ] dest=/tmp/tmpdr_romr3/weights size="172 MB" total_elapsed=2.100s url=https://replicate.delivery/yhqm/wcEw4wgidoaBNRtwPlbPsmE6NrOpjtJhYlqYKQsJGC26YT2E/trained_model.tar Downloaded weights in 2.12s Loaded LoRAs in 18.37s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:27, 1.01s/it] 7%|▋ | 2/28 [00:01<00:23, 1.12it/s] 11%|█ | 3/28 [00:02<00:23, 1.06it/s] 14%|█▍ | 4/28 [00:03<00:23, 1.03it/s] 18%|█▊ | 5/28 [00:04<00:22, 1.02it/s] 21%|██▏ | 6/28 [00:05<00:21, 1.01it/s] 25%|██▌ | 7/28 [00:06<00:20, 1.01it/s] 29%|██▊ | 8/28 [00:07<00:19, 1.00it/s] 32%|███▏ | 9/28 [00:08<00:19, 1.00s/it] 36%|███▌ | 10/28 [00:09<00:18, 1.01s/it] 39%|███▉ | 11/28 [00:10<00:17, 1.01s/it] 43%|████▎ | 12/28 [00:11<00:16, 1.01s/it] 46%|████▋ | 13/28 [00:12<00:15, 1.01s/it] 50%|█████ | 14/28 [00:13<00:14, 1.01s/it] 54%|█████▎ | 15/28 [00:14<00:13, 1.01s/it] 57%|█████▋ | 16/28 [00:15<00:12, 1.01s/it] 61%|██████ | 17/28 [00:16<00:11, 1.01s/it] 64%|██████▍ | 18/28 [00:17<00:10, 1.01s/it] 68%|██████▊ | 19/28 [00:18<00:09, 1.01s/it] 71%|███████▏ | 20/28 [00:19<00:08, 1.01s/it] 75%|███████▌ | 21/28 [00:20<00:07, 1.01s/it] 79%|███████▊ | 22/28 [00:21<00:06, 1.01s/it] 82%|████████▏ | 23/28 [00:23<00:05, 1.01s/it] 86%|████████▌ | 24/28 [00:24<00:04, 1.01s/it] 89%|████████▉ | 25/28 [00:25<00:03, 1.01s/it] 93%|█████████▎| 26/28 [00:26<00:02, 1.01s/it] 96%|█████████▋| 27/28 [00:27<00:01, 1.01s/it] 100%|██████████| 28/28 [00:28<00:00, 1.01s/it] 100%|██████████| 28/28 [00:28<00:00, 1.00s/it]
Want to make some of these yourself?
Run this model
