igorriti / flux-360
Generate 360 panorama images.
Prediction
igorriti/flux-360:7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211eID0qkyawhcjnrm60chk7brybxjdrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- A 3d render of a futiristic landscape. There's a city with stone building at the background and a forest. 360 view in the style of TOK
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 3:2
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 50
{ "model": "dev", "prompt": "A 3d render of a futiristic landscape. There's a city with stone building at the background and a forest. 360 view in the style of TOK", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 50 }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 igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "igorriti/flux-360:7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211e", { input: { model: "dev", prompt: "A 3d render of a futiristic landscape. There's a city with stone building at the background and a forest. 360 view in the style of TOK", lora_scale: 1, num_outputs: 4, aspect_ratio: "3:2", output_format: "webp", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 50 } } ); // 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 igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "igorriti/flux-360:7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211e", input={ "model": "dev", "prompt": "A 3d render of a futiristic landscape. There's a city with stone building at the background and a forest. 360 view in the style of TOK", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 50 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run igorriti/flux-360 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": "igorriti/flux-360:7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211e", "input": { "model": "dev", "prompt": "A 3d render of a futiristic landscape. There\'s a city with stone building at the background and a forest. 360 view in the style of TOK", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-28T16:36:25.462381Z", "created_at": "2024-08-28T16:35:01.397000Z", "data_removed": false, "error": null, "id": "0qkyawhcjnrm60chk7brybxjdr", "input": { "model": "dev", "prompt": "A 3d render of a futiristic landscape. There's a city with stone building at the background and a forest. 360 view in the style of TOK", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 59130\nPrompt: A 3d render of a futiristic landscape. There's a city with stone building at the background and a forest. 360 view in the style of TOK\ntxt2img mode\nUsing dev model\nfree=9529842020352\nDownloading weights\n2024-08-28T16:35:01Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpi2182c9z/weights url=https://replicate.delivery/yhqm/JadMcXHmesynVK8UUvwBtfJbWWtg44dMcireTuH5jkXdjdumA/trained_model.tar\n2024-08-28T16:35:03Z | INFO | [ Complete ] dest=/tmp/tmpi2182c9z/weights size=\"172 MB\" total_elapsed=2.222s url=https://replicate.delivery/yhqm/JadMcXHmesynVK8UUvwBtfJbWWtg44dMcireTuH5jkXdjdumA/trained_model.tar\nDownloaded weights in 2.25s\nLoaded LoRAs in 34.04s\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:47, 1.04it/s]\n 4%|▍ | 2/50 [00:01<00:40, 1.18it/s]\n 6%|▌ | 3/50 [00:02<00:42, 1.11it/s]\n 8%|▊ | 4/50 [00:03<00:42, 1.08it/s]\n 10%|█ | 5/50 [00:04<00:42, 1.06it/s]\n 12%|█▏ | 6/50 [00:05<00:41, 1.05it/s]\n 14%|█▍ | 7/50 [00:06<00:41, 1.04it/s]\n 16%|█▌ | 8/50 [00:07<00:40, 1.04it/s]\n 18%|█▊ | 9/50 [00:08<00:39, 1.04it/s]\n 20%|██ | 10/50 [00:09<00:38, 1.04it/s]\n 22%|██▏ | 11/50 [00:10<00:37, 1.03it/s]\n 24%|██▍ | 12/50 [00:11<00:36, 1.03it/s]\n 26%|██▌ | 13/50 [00:12<00:35, 1.03it/s]\n 28%|██▊ | 14/50 [00:13<00:34, 1.03it/s]\n 30%|███ | 15/50 [00:14<00:33, 1.03it/s]\n 32%|███▏ | 16/50 [00:15<00:32, 1.03it/s]\n 34%|███▍ | 17/50 [00:16<00:31, 1.03it/s]\n 36%|███▌ | 18/50 [00:17<00:31, 1.03it/s]\n 38%|███▊ | 19/50 [00:18<00:30, 1.03it/s]\n 40%|████ | 20/50 [00:19<00:29, 1.03it/s]\n 42%|████▏ | 21/50 [00:20<00:28, 1.03it/s]\n 44%|████▍ | 22/50 [00:21<00:27, 1.03it/s]\n 46%|████▌ | 23/50 [00:22<00:26, 1.03it/s]\n 48%|████▊ | 24/50 [00:23<00:25, 1.03it/s]\n 50%|█████ | 25/50 [00:24<00:24, 1.03it/s]\n 52%|█████▏ | 26/50 [00:25<00:23, 1.03it/s]\n 54%|█████▍ | 27/50 [00:25<00:22, 1.03it/s]\n 56%|█████▌ | 28/50 [00:26<00:21, 1.03it/s]\n 58%|█████▊ | 29/50 [00:27<00:20, 1.03it/s]\n 60%|██████ | 30/50 [00:28<00:19, 1.03it/s]\n 62%|██████▏ | 31/50 [00:29<00:18, 1.03it/s]\n 64%|██████▍ | 32/50 [00:30<00:17, 1.03it/s]\n 66%|██████▌ | 33/50 [00:31<00:16, 1.03it/s]\n 68%|██████▊ | 34/50 [00:32<00:15, 1.03it/s]\n 70%|███████ | 35/50 [00:33<00:14, 1.03it/s]\n 72%|███████▏ | 36/50 [00:34<00:13, 1.03it/s]\n 74%|███████▍ | 37/50 [00:35<00:12, 1.03it/s]\n 76%|███████▌ | 38/50 [00:36<00:11, 1.03it/s]\n 78%|███████▊ | 39/50 [00:37<00:10, 1.03it/s]\n 80%|████████ | 40/50 [00:38<00:09, 1.03it/s]\n 82%|████████▏ | 41/50 [00:39<00:08, 1.03it/s]\n 84%|████████▍ | 42/50 [00:40<00:07, 1.03it/s]\n 86%|████████▌ | 43/50 [00:41<00:06, 1.03it/s]\n 88%|████████▊ | 44/50 [00:42<00:05, 1.03it/s]\n 90%|█████████ | 45/50 [00:43<00:04, 1.03it/s]\n 92%|█████████▏| 46/50 [00:44<00:03, 1.03it/s]\n 94%|█████████▍| 47/50 [00:45<00:02, 1.03it/s]\n 96%|█████████▌| 48/50 [00:46<00:01, 1.03it/s]\n 98%|█████████▊| 49/50 [00:47<00:00, 1.03it/s]\n100%|██████████| 50/50 [00:48<00:00, 1.03it/s]\n100%|██████████| 50/50 [00:48<00:00, 1.04it/s]", "metrics": { "predict_time": 84.055762276, "total_time": 84.065381 }, "output": [ "https://replicate.delivery/yhqm/kKogbW6eCfuqfJikHD8eiVUd2jDlbiSHZ5IDGmuheaBLBC6aC/out-0.webp", "https://replicate.delivery/yhqm/NmeJgkuVXoxpUa1f0iRq9MWGtUZWOcix36nlosDmN0rJQQXTA/out-1.webp", "https://replicate.delivery/yhqm/T89sCMeaiLQxHSAZxEtQ6sAF1jDCpFs5zrhTfNMdRYVJQQXTA/out-2.webp", "https://replicate.delivery/yhqm/EO05xl1I4R5JJpkgh9YlMk3wEw7mkuXMZfZuKgYUuruEIorJA/out-3.webp" ], "started_at": "2024-08-28T16:35:01.406619Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/0qkyawhcjnrm60chk7brybxjdr", "cancel": "https://api.replicate.com/v1/predictions/0qkyawhcjnrm60chk7brybxjdr/cancel" }, "version": "7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211e" }Generated inUsing seed: 59130 Prompt: A 3d render of a futiristic landscape. There's a city with stone building at the background and a forest. 360 view in the style of TOK txt2img mode Using dev model free=9529842020352 Downloading weights 2024-08-28T16:35:01Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpi2182c9z/weights url=https://replicate.delivery/yhqm/JadMcXHmesynVK8UUvwBtfJbWWtg44dMcireTuH5jkXdjdumA/trained_model.tar 2024-08-28T16:35:03Z | INFO | [ Complete ] dest=/tmp/tmpi2182c9z/weights size="172 MB" total_elapsed=2.222s url=https://replicate.delivery/yhqm/JadMcXHmesynVK8UUvwBtfJbWWtg44dMcireTuH5jkXdjdumA/trained_model.tar Downloaded weights in 2.25s Loaded LoRAs in 34.04s 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:47, 1.04it/s] 4%|▍ | 2/50 [00:01<00:40, 1.18it/s] 6%|▌ | 3/50 [00:02<00:42, 1.11it/s] 8%|▊ | 4/50 [00:03<00:42, 1.08it/s] 10%|█ | 5/50 [00:04<00:42, 1.06it/s] 12%|█▏ | 6/50 [00:05<00:41, 1.05it/s] 14%|█▍ | 7/50 [00:06<00:41, 1.04it/s] 16%|█▌ | 8/50 [00:07<00:40, 1.04it/s] 18%|█▊ | 9/50 [00:08<00:39, 1.04it/s] 20%|██ | 10/50 [00:09<00:38, 1.04it/s] 22%|██▏ | 11/50 [00:10<00:37, 1.03it/s] 24%|██▍ | 12/50 [00:11<00:36, 1.03it/s] 26%|██▌ | 13/50 [00:12<00:35, 1.03it/s] 28%|██▊ | 14/50 [00:13<00:34, 1.03it/s] 30%|███ | 15/50 [00:14<00:33, 1.03it/s] 32%|███▏ | 16/50 [00:15<00:32, 1.03it/s] 34%|███▍ | 17/50 [00:16<00:31, 1.03it/s] 36%|███▌ | 18/50 [00:17<00:31, 1.03it/s] 38%|███▊ | 19/50 [00:18<00:30, 1.03it/s] 40%|████ | 20/50 [00:19<00:29, 1.03it/s] 42%|████▏ | 21/50 [00:20<00:28, 1.03it/s] 44%|████▍ | 22/50 [00:21<00:27, 1.03it/s] 46%|████▌ | 23/50 [00:22<00:26, 1.03it/s] 48%|████▊ | 24/50 [00:23<00:25, 1.03it/s] 50%|█████ | 25/50 [00:24<00:24, 1.03it/s] 52%|█████▏ | 26/50 [00:25<00:23, 1.03it/s] 54%|█████▍ | 27/50 [00:25<00:22, 1.03it/s] 56%|█████▌ | 28/50 [00:26<00:21, 1.03it/s] 58%|█████▊ | 29/50 [00:27<00:20, 1.03it/s] 60%|██████ | 30/50 [00:28<00:19, 1.03it/s] 62%|██████▏ | 31/50 [00:29<00:18, 1.03it/s] 64%|██████▍ | 32/50 [00:30<00:17, 1.03it/s] 66%|██████▌ | 33/50 [00:31<00:16, 1.03it/s] 68%|██████▊ | 34/50 [00:32<00:15, 1.03it/s] 70%|███████ | 35/50 [00:33<00:14, 1.03it/s] 72%|███████▏ | 36/50 [00:34<00:13, 1.03it/s] 74%|███████▍ | 37/50 [00:35<00:12, 1.03it/s] 76%|███████▌ | 38/50 [00:36<00:11, 1.03it/s] 78%|███████▊ | 39/50 [00:37<00:10, 1.03it/s] 80%|████████ | 40/50 [00:38<00:09, 1.03it/s] 82%|████████▏ | 41/50 [00:39<00:08, 1.03it/s] 84%|████████▍ | 42/50 [00:40<00:07, 1.03it/s] 86%|████████▌ | 43/50 [00:41<00:06, 1.03it/s] 88%|████████▊ | 44/50 [00:42<00:05, 1.03it/s] 90%|█████████ | 45/50 [00:43<00:04, 1.03it/s] 92%|█████████▏| 46/50 [00:44<00:03, 1.03it/s] 94%|█████████▍| 47/50 [00:45<00:02, 1.03it/s] 96%|█████████▌| 48/50 [00:46<00:01, 1.03it/s] 98%|█████████▊| 49/50 [00:47<00:00, 1.03it/s] 100%|██████████| 50/50 [00:48<00:00, 1.03it/s] 100%|██████████| 50/50 [00:48<00:00, 1.04it/s]Prediction
igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28IDas2hk7t24xrm40chj27t8x8k30StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- an ultra realistic beach, in the style of TOK
- lora_scale
- 1
- num_outputs
- 3
- aspect_ratio
- 16:9
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 49
{ "model": "dev", "prompt": "an ultra realistic beach, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 }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 igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28", { input: { model: "dev", prompt: "an ultra realistic beach, in the style of TOK", lora_scale: 1, num_outputs: 3, aspect_ratio: "16:9", output_format: "png", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 49 } } ); // 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 igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28", input={ "model": "dev", "prompt": "an ultra realistic beach, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run igorriti/flux-360 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": "igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28", "input": { "model": "dev", "prompt": "an ultra realistic beach, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T21:20:44.176137Z", "created_at": "2024-08-26T21:19:53.383000Z", "data_removed": false, "error": null, "id": "as2hk7t24xrm40chj27t8x8k30", "input": { "model": "dev", "prompt": "an ultra realistic beach, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 }, "logs": "Using seed: 4931\nPrompt: an ultra realistic beach, in the style of TOK\ntxt2img mode\nUsing dev model\nfree=10076565909504\nDownloading weights\n2024-08-26T21:19:53Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpcdpggx2v/weights url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar\n2024-08-26T21:19:55Z | INFO | [ Complete ] dest=/tmp/tmpcdpggx2v/weights size=\"172 MB\" total_elapsed=1.749s url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar\nDownloaded weights in 1.79s\nLoaded LoRAs in 11.62s\n 0%| | 0/49 [00:00<?, ?it/s]\n 2%|▏ | 1/49 [00:00<00:35, 1.34it/s]\n 4%|▍ | 2/49 [00:01<00:30, 1.53it/s]\n 6%|▌ | 3/49 [00:02<00:32, 1.43it/s]\n 8%|▊ | 4/49 [00:02<00:32, 1.39it/s]\n 10%|█ | 5/49 [00:03<00:32, 1.36it/s]\n 12%|█▏ | 6/49 [00:04<00:31, 1.35it/s]\n 14%|█▍ | 7/49 [00:05<00:31, 1.34it/s]\n 16%|█▋ | 8/49 [00:05<00:30, 1.34it/s]\n 18%|█▊ | 9/49 [00:06<00:30, 1.33it/s]\n 20%|██ | 10/49 [00:07<00:29, 1.33it/s]\n 22%|██▏ | 11/49 [00:08<00:28, 1.33it/s]\n 24%|██▍ | 12/49 [00:08<00:27, 1.33it/s]\n 27%|██▋ | 13/49 [00:09<00:27, 1.33it/s]\n 29%|██▊ | 14/49 [00:10<00:26, 1.33it/s]\n 31%|███ | 15/49 [00:11<00:25, 1.33it/s]\n 33%|███▎ | 16/49 [00:11<00:24, 1.32it/s]\n 35%|███▍ | 17/49 [00:12<00:24, 1.32it/s]\n 37%|███▋ | 18/49 [00:13<00:23, 1.32it/s]\n 39%|███▉ | 19/49 [00:14<00:22, 1.33it/s]\n 41%|████ | 20/49 [00:14<00:21, 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[00:31<00:05, 1.32it/s]\n 88%|████████▊ | 43/49 [00:32<00:04, 1.32it/s]\n 90%|████████▉ | 44/49 [00:33<00:03, 1.32it/s]\n 92%|█████████▏| 45/49 [00:33<00:03, 1.32it/s]\n 94%|█████████▍| 46/49 [00:34<00:02, 1.32it/s]\n 96%|█████████▌| 47/49 [00:35<00:01, 1.32it/s]\n 98%|█████████▊| 48/49 [00:36<00:00, 1.32it/s]\n100%|██████████| 49/49 [00:36<00:00, 1.32it/s]\n100%|██████████| 49/49 [00:36<00:00, 1.33it/s]", "metrics": { "predict_time": 50.782432038, "total_time": 50.793137 }, "output": [ "https://replicate.delivery/yhqm/yjYOeLpv0NVaa6Ql1eTBWCRJl7XPZOAReBoFrcszJspWdUtmA/out-0.png", "https://replicate.delivery/yhqm/eqw5HFiyObWAZisjFtvUEJZ5aHSwfAWLe3SQlzw6QC1WdUtmA/out-1.png", "https://replicate.delivery/yhqm/Oej42MQyzjxZFCYnDCaT8F2TWLORjv9PVm3CBJA5O2CWHVrJA/out-2.png" ], "started_at": "2024-08-26T21:19:53.393705Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/as2hk7t24xrm40chj27t8x8k30", "cancel": "https://api.replicate.com/v1/predictions/as2hk7t24xrm40chj27t8x8k30/cancel" }, "version": "6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28" }Generated inUsing seed: 4931 Prompt: an ultra realistic beach, in the style of TOK txt2img mode Using dev model free=10076565909504 Downloading weights 2024-08-26T21:19:53Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpcdpggx2v/weights url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar 2024-08-26T21:19:55Z | INFO | [ Complete ] dest=/tmp/tmpcdpggx2v/weights size="172 MB" total_elapsed=1.749s url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar Downloaded weights in 1.79s Loaded LoRAs in 11.62s 0%| | 0/49 [00:00<?, ?it/s] 2%|▏ | 1/49 [00:00<00:35, 1.34it/s] 4%|▍ | 2/49 [00:01<00:30, 1.53it/s] 6%|▌ | 3/49 [00:02<00:32, 1.43it/s] 8%|▊ | 4/49 [00:02<00:32, 1.39it/s] 10%|█ | 5/49 [00:03<00:32, 1.36it/s] 12%|█▏ | 6/49 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igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28IDj4d260qjk9rm40chj28aww8gqrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- an ultra realistic forest, 360 view, in the style of TOK
- lora_scale
- 1
- num_outputs
- 3
- aspect_ratio
- 16:9
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 49
{ "model": "dev", "prompt": "an ultra realistic forest, 360 view, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 }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 igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28", { input: { model: "dev", prompt: "an ultra realistic forest, 360 view, in the style of TOK", lora_scale: 1, num_outputs: 3, aspect_ratio: "16:9", output_format: "png", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 49 } } ); // 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 igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28", input={ "model": "dev", "prompt": "an ultra realistic forest, 360 view, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run igorriti/flux-360 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": "igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28", "input": { "model": "dev", "prompt": "an ultra realistic forest, 360 view, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T21:22:35.410364Z", "created_at": "2024-08-26T21:21:44.090000Z", "data_removed": false, "error": null, "id": "j4d260qjk9rm40chj28aww8gqr", "input": { "model": "dev", "prompt": "an ultra realistic forest, 360 view, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 }, "logs": "Using seed: 46002\nPrompt: an ultra realistic forest, 360 view, in the style of TOK\ntxt2img mode\nUsing dev model\nfree=9081665400832\nDownloading weights\n2024-08-26T21:21:44Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpd3545cu1/weights url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar\n2024-08-26T21:21:47Z | INFO | [ Complete ] dest=/tmp/tmpd3545cu1/weights size=\"172 MB\" total_elapsed=3.137s url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar\nDownloaded weights in 3.17s\nLoaded LoRAs in 12.03s\n 0%| | 0/49 [00:00<?, ?it/s]\n 2%|▏ | 1/49 [00:00<00:36, 1.32it/s]\n 4%|▍ | 2/49 [00:01<00:31, 1.51it/s]\n 6%|▌ | 3/49 [00:02<00:32, 1.41it/s]\n 8%|▊ | 4/49 [00:02<00:32, 1.37it/s]\n 10%|█ | 5/49 [00:03<00:32, 1.35it/s]\n 12%|█▏ | 6/49 [00:04<00:32, 1.34it/s]\n 14%|█▍ | 7/49 [00:05<00:31, 1.33it/s]\n 16%|█▋ | 8/49 [00:05<00:30, 1.33it/s]\n 18%|█▊ | 9/49 [00:06<00:30, 1.32it/s]\n 20%|██ | 10/49 [00:07<00:29, 1.32it/s]\n 22%|██▏ | 11/49 [00:08<00:28, 1.32it/s]\n 24%|██▍ | 12/49 [00:08<00:28, 1.32it/s]\n 27%|██▋ | 13/49 [00:09<00:27, 1.32it/s]\n 29%|██▊ | 14/49 [00:10<00:26, 1.31it/s]\n 31%|███ | 15/49 [00:11<00:25, 1.31it/s]\n 33%|███▎ | 16/49 [00:12<00:25, 1.31it/s]\n 35%|███▍ | 17/49 [00:12<00:24, 1.31it/s]\n 37%|███▋ | 18/49 [00:13<00:23, 1.31it/s]\n 39%|███▉ | 19/49 [00:14<00:22, 1.31it/s]\n 41%|████ | 20/49 [00:15<00:22, 1.31it/s]\n 43%|████▎ | 21/49 [00:15<00:21, 1.31it/s]\n 45%|████▍ | 22/49 [00:16<00:20, 1.31it/s]\n 47%|████▋ | 23/49 [00:17<00:19, 1.31it/s]\n 49%|████▉ | 24/49 [00:18<00:19, 1.31it/s]\n 51%|█████ | 25/49 [00:18<00:18, 1.31it/s]\n 53%|█████▎ | 26/49 [00:19<00:17, 1.31it/s]\n 55%|█████▌ | 27/49 [00:20<00:16, 1.31it/s]\n 57%|█████▋ | 28/49 [00:21<00:16, 1.31it/s]\n 59%|█████▉ | 29/49 [00:21<00:15, 1.31it/s]\n 61%|██████ | 30/49 [00:22<00:14, 1.31it/s]\n 63%|██████▎ | 31/49 [00:23<00:13, 1.31it/s]\n 65%|██████▌ | 32/49 [00:24<00:12, 1.31it/s]\n 67%|██████▋ | 33/49 [00:24<00:12, 1.31it/s]\n 69%|██████▉ | 34/49 [00:25<00:11, 1.31it/s]\n 71%|███████▏ | 35/49 [00:26<00:10, 1.31it/s]\n 73%|███████▎ | 36/49 [00:27<00:09, 1.31it/s]\n 76%|███████▌ | 37/49 [00:28<00:09, 1.31it/s]\n 78%|███████▊ | 38/49 [00:28<00:08, 1.31it/s]\n 80%|███████▉ | 39/49 [00:29<00:07, 1.31it/s]\n 82%|████████▏ | 40/49 [00:30<00:06, 1.31it/s]\n 84%|████████▎ | 41/49 [00:31<00:06, 1.31it/s]\n 86%|████████▌ | 42/49 [00:31<00:05, 1.31it/s]\n 88%|████████▊ | 43/49 [00:32<00:04, 1.31it/s]\n 90%|████████▉ | 44/49 [00:33<00:03, 1.31it/s]\n 92%|█████████▏| 45/49 [00:34<00:03, 1.31it/s]\n 94%|█████████▍| 46/49 [00:34<00:02, 1.31it/s]\n 96%|█████████▌| 47/49 [00:35<00:01, 1.31it/s]\n 98%|█████████▊| 48/49 [00:36<00:00, 1.31it/s]\n100%|██████████| 49/49 [00:37<00:00, 1.31it/s]\n100%|██████████| 49/49 [00:37<00:00, 1.32it/s]", "metrics": { "predict_time": 51.225681395, "total_time": 51.320364 }, "output": [ "https://replicate.delivery/yhqm/cCd8VMSxVuZTLdTTOFIni60eCZXLZ2Tjn0G9d7eqpymaQqWTA/out-0.png", "https://replicate.delivery/yhqm/yFKYf3q7P6Q8WSVuCUoHadwe3VmqTeGWSKMnqer0YjDvBpaNB/out-1.png", "https://replicate.delivery/yhqm/e7L5IVJmeTkpWkDbw6vuWJ2i8geDw94SIG5x0SIbRuftBpaNB/out-2.png" ], "started_at": "2024-08-26T21:21:44.184683Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/j4d260qjk9rm40chj28aww8gqr", "cancel": "https://api.replicate.com/v1/predictions/j4d260qjk9rm40chj28aww8gqr/cancel" }, "version": "6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28" }Generated inUsing seed: 46002 Prompt: an ultra realistic forest, 360 view, in the style of TOK txt2img mode Using dev model free=9081665400832 Downloading weights 2024-08-26T21:21:44Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpd3545cu1/weights url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar 2024-08-26T21:21:47Z | INFO | [ Complete ] dest=/tmp/tmpd3545cu1/weights size="172 MB" total_elapsed=3.137s url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar Downloaded weights in 3.17s Loaded LoRAs in 12.03s 0%| | 0/49 [00:00<?, ?it/s] 2%|▏ | 1/49 [00:00<00:36, 1.32it/s] 4%|▍ | 2/49 [00:01<00:31, 1.51it/s] 6%|▌ | 3/49 [00:02<00:32, 1.41it/s] 8%|▊ | 4/49 [00:02<00:32, 1.37it/s] 10%|█ | 5/49 [00:03<00:32, 1.35it/s] 12%|█▏ | 6/49 [00:04<00:32, 1.34it/s] 14%|█▍ | 7/49 [00:05<00:31, 1.33it/s] 16%|█▋ | 8/49 [00:05<00:30, 1.33it/s] 18%|█▊ | 9/49 [00:06<00:30, 1.32it/s] 20%|██ | 10/49 [00:07<00:29, 1.32it/s] 22%|██▏ | 11/49 [00:08<00:28, 1.32it/s] 24%|██▍ | 12/49 [00:08<00:28, 1.32it/s] 27%|██▋ | 13/49 [00:09<00:27, 1.32it/s] 29%|██▊ | 14/49 [00:10<00:26, 1.31it/s] 31%|███ | 15/49 [00:11<00:25, 1.31it/s] 33%|███▎ | 16/49 [00:12<00:25, 1.31it/s] 35%|███▍ | 17/49 [00:12<00:24, 1.31it/s] 37%|███▋ | 18/49 [00:13<00:23, 1.31it/s] 39%|███▉ | 19/49 [00:14<00:22, 1.31it/s] 41%|████ | 20/49 [00:15<00:22, 1.31it/s] 43%|████▎ | 21/49 [00:15<00:21, 1.31it/s] 45%|████▍ | 22/49 [00:16<00:20, 1.31it/s] 47%|████▋ | 23/49 [00:17<00:19, 1.31it/s] 49%|████▉ | 24/49 [00:18<00:19, 1.31it/s] 51%|█████ | 25/49 [00:18<00:18, 1.31it/s] 53%|█████▎ | 26/49 [00:19<00:17, 1.31it/s] 55%|█████▌ | 27/49 [00:20<00:16, 1.31it/s] 57%|█████▋ | 28/49 [00:21<00:16, 1.31it/s] 59%|█████▉ | 29/49 [00:21<00:15, 1.31it/s] 61%|██████ | 30/49 [00:22<00:14, 1.31it/s] 63%|██████▎ | 31/49 [00:23<00:13, 1.31it/s] 65%|██████▌ | 32/49 [00:24<00:12, 1.31it/s] 67%|██████▋ | 33/49 [00:24<00:12, 1.31it/s] 69%|██████▉ | 34/49 [00:25<00:11, 1.31it/s] 71%|███████▏ | 35/49 [00:26<00:10, 1.31it/s] 73%|███████▎ | 36/49 [00:27<00:09, 1.31it/s] 76%|███████▌ | 37/49 [00:28<00:09, 1.31it/s] 78%|███████▊ | 38/49 [00:28<00:08, 1.31it/s] 80%|███████▉ | 39/49 [00:29<00:07, 1.31it/s] 82%|████████▏ | 40/49 [00:30<00:06, 1.31it/s] 84%|████████▎ | 41/49 [00:31<00:06, 1.31it/s] 86%|████████▌ | 42/49 [00:31<00:05, 1.31it/s] 88%|████████▊ | 43/49 [00:32<00:04, 1.31it/s] 90%|████████▉ | 44/49 [00:33<00:03, 1.31it/s] 92%|█████████▏| 45/49 [00:34<00:03, 1.31it/s] 94%|█████████▍| 46/49 [00:34<00:02, 1.31it/s] 96%|█████████▌| 47/49 [00:35<00:01, 1.31it/s] 98%|█████████▊| 48/49 [00:36<00:00, 1.31it/s] 100%|██████████| 49/49 [00:37<00:00, 1.31it/s] 100%|██████████| 49/49 [00:37<00:00, 1.32it/s]Prediction
igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28IDv9x160wsrdrm40chjff8e23ctcStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- painting of a sea with a pirate ship at the distance, 360 view, in the style of TOK
- lora_scale
- 1
- num_outputs
- 3
- aspect_ratio
- 16:9
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 49
{ "model": "dev", "prompt": "painting of a sea with a pirate ship at the distance, 360 view, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 }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 igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28", { input: { model: "dev", prompt: "painting of a sea with a pirate ship at the distance, 360 view, in the style of TOK", lora_scale: 1, num_outputs: 3, aspect_ratio: "16:9", output_format: "png", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 49 } } ); // 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 igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28", input={ "model": "dev", "prompt": "painting of a sea with a pirate ship at the distance, 360 view, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run igorriti/flux-360 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": "igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28", "input": { "model": "dev", "prompt": "painting of a sea with a pirate ship at the distance, 360 view, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-27T12:47:03.008577Z", "created_at": "2024-08-27T12:45:24.803000Z", "data_removed": false, "error": null, "id": "v9x160wsrdrm40chjff8e23ctc", "input": { "model": "dev", "prompt": "painting of a sea with a pirate ship at the distance, 360 view, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 }, "logs": "Using seed: 15699\nPrompt: painting of a sea with a pirate ship at the distance, 360 view, in the style of TOK\ntxt2img mode\nUsing dev model\nfree=9579092705280\nDownloading weights\n2024-08-27T12:46:15Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpa1ehw63r/weights url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar\n2024-08-27T12:46:16Z | INFO | [ Complete ] dest=/tmp/tmpa1ehw63r/weights size=\"172 MB\" total_elapsed=1.254s url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar\nDownloaded weights in 1.29s\nLoaded LoRAs in 8.60s\n 0%| | 0/49 [00:00<?, ?it/s]\n 2%|▏ | 1/49 [00:00<00:36, 1.33it/s]\n 4%|▍ | 2/49 [00:01<00:30, 1.52it/s]\n 6%|▌ | 3/49 [00:02<00:32, 1.42it/s]\n 8%|▊ | 4/49 [00:02<00:32, 1.38it/s]\n 10%|█ | 5/49 [00:03<00:32, 1.36it/s]\n 12%|█▏ | 6/49 [00:04<00:31, 1.34it/s]\n 14%|█▍ | 7/49 [00:05<00:31, 1.34it/s]\n 16%|█▋ | 8/49 [00:05<00:30, 1.33it/s]\n 18%|█▊ | 9/49 [00:06<00:30, 1.33it/s]\n 20%|██ | 10/49 [00:07<00:29, 1.33it/s]\n 22%|██▏ | 11/49 [00:08<00:28, 1.32it/s]\n 24%|██▍ | 12/49 [00:08<00:27, 1.32it/s]\n 27%|██▋ | 13/49 [00:09<00:27, 1.32it/s]\n 29%|██▊ | 14/49 [00:10<00:26, 1.32it/s]\n 31%|███ | 15/49 [00:11<00:25, 1.32it/s]\n 33%|███▎ | 16/49 [00:11<00:24, 1.32it/s]\n 35%|███▍ | 17/49 [00:12<00:24, 1.32it/s]\n 37%|███▋ | 18/49 [00:13<00:23, 1.32it/s]\n 39%|███▉ | 19/49 [00:14<00:22, 1.32it/s]\n 41%|████ | 20/49 [00:14<00:22, 1.32it/s]\n 43%|████▎ | 21/49 [00:15<00:21, 1.32it/s]\n 45%|████▍ | 22/49 [00:16<00:20, 1.32it/s]\n 47%|████▋ | 23/49 [00:17<00:19, 1.32it/s]\n 49%|████▉ | 24/49 [00:18<00:18, 1.32it/s]\n 51%|█████ | 25/49 [00:18<00:18, 1.32it/s]\n 53%|█████▎ | 26/49 [00:19<00:17, 1.32it/s]\n 55%|█████▌ | 27/49 [00:20<00:16, 1.32it/s]\n 57%|█████▋ | 28/49 [00:21<00:15, 1.32it/s]\n 59%|█████▉ | 29/49 [00:21<00:15, 1.32it/s]\n 61%|██████ | 30/49 [00:22<00:14, 1.32it/s]\n 63%|██████▎ | 31/49 [00:23<00:13, 1.32it/s]\n 65%|██████▌ | 32/49 [00:24<00:12, 1.32it/s]\n 67%|██████▋ | 33/49 [00:24<00:12, 1.32it/s]\n 69%|██████▉ | 34/49 [00:25<00:11, 1.32it/s]\n 71%|███████▏ | 35/49 [00:26<00:10, 1.32it/s]\n 73%|███████▎ | 36/49 [00:27<00:09, 1.32it/s]\n 76%|███████▌ | 37/49 [00:27<00:09, 1.32it/s]\n 78%|███████▊ | 38/49 [00:28<00:08, 1.32it/s]\n 80%|███████▉ | 39/49 [00:29<00:07, 1.32it/s]\n 82%|████████▏ | 40/49 [00:30<00:06, 1.32it/s]\n 84%|████████▎ | 41/49 [00:30<00:06, 1.32it/s]\n 86%|████████▌ | 42/49 [00:31<00:05, 1.32it/s]\n 88%|████████▊ | 43/49 [00:32<00:04, 1.32it/s]\n 90%|████████▉ | 44/49 [00:33<00:03, 1.32it/s]\n 92%|█████████▏| 45/49 [00:33<00:03, 1.32it/s]\n 94%|█████████▍| 46/49 [00:34<00:02, 1.32it/s]\n 96%|█████████▌| 47/49 [00:35<00:01, 1.32it/s]\n 98%|█████████▊| 48/49 [00:36<00:00, 1.32it/s]\n100%|██████████| 49/49 [00:37<00:00, 1.32it/s]\n100%|██████████| 49/49 [00:37<00:00, 1.32it/s]", "metrics": { "predict_time": 47.898215481, "total_time": 98.205577 }, "output": [ "https://replicate.delivery/yhqm/sF0hvPuYY7reL6MTnjeWR8jxeqBd3uLSYYoSpgShnZmNmvtmA/out-0.png", "https://replicate.delivery/yhqm/IJfgzHXZbZzENKF5JYxAexpoqd2nQrLYD1ec4peNmlTbMf2aC/out-1.png", "https://replicate.delivery/yhqm/k3r3EtSNU0aGCN7AWInoeUxBZdJXwOJiNalO3WZOTXZj5brJA/out-2.png" ], "started_at": "2024-08-27T12:46:15.110361Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/v9x160wsrdrm40chjff8e23ctc", "cancel": "https://api.replicate.com/v1/predictions/v9x160wsrdrm40chjff8e23ctc/cancel" }, "version": "6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28" }Generated inUsing seed: 15699 Prompt: painting of a sea with a pirate ship at the distance, 360 view, in the style of TOK txt2img mode Using dev model free=9579092705280 Downloading weights 2024-08-27T12:46:15Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpa1ehw63r/weights url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar 2024-08-27T12:46:16Z | INFO | [ Complete ] dest=/tmp/tmpa1ehw63r/weights size="172 MB" total_elapsed=1.254s url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar Downloaded weights in 1.29s Loaded LoRAs in 8.60s 0%| | 0/49 [00:00<?, ?it/s] 2%|▏ | 1/49 [00:00<00:36, 1.33it/s] 4%|▍ | 2/49 [00:01<00:30, 1.52it/s] 6%|▌ | 3/49 [00:02<00:32, 1.42it/s] 8%|▊ | 4/49 [00:02<00:32, 1.38it/s] 10%|█ | 5/49 [00:03<00:32, 1.36it/s] 12%|█▏ | 6/49 [00:04<00:31, 1.34it/s] 14%|█▍ | 7/49 [00:05<00:31, 1.34it/s] 16%|█▋ | 8/49 [00:05<00:30, 1.33it/s] 18%|█▊ | 9/49 [00:06<00:30, 1.33it/s] 20%|██ | 10/49 [00:07<00:29, 1.33it/s] 22%|██▏ | 11/49 [00:08<00:28, 1.32it/s] 24%|██▍ | 12/49 [00:08<00:27, 1.32it/s] 27%|██▋ | 13/49 [00:09<00:27, 1.32it/s] 29%|██▊ | 14/49 [00:10<00:26, 1.32it/s] 31%|███ | 15/49 [00:11<00:25, 1.32it/s] 33%|███▎ | 16/49 [00:11<00:24, 1.32it/s] 35%|███▍ | 17/49 [00:12<00:24, 1.32it/s] 37%|███▋ | 18/49 [00:13<00:23, 1.32it/s] 39%|███▉ | 19/49 [00:14<00:22, 1.32it/s] 41%|████ | 20/49 [00:14<00:22, 1.32it/s] 43%|████▎ | 21/49 [00:15<00:21, 1.32it/s] 45%|████▍ | 22/49 [00:16<00:20, 1.32it/s] 47%|████▋ | 23/49 [00:17<00:19, 1.32it/s] 49%|████▉ | 24/49 [00:18<00:18, 1.32it/s] 51%|█████ | 25/49 [00:18<00:18, 1.32it/s] 53%|█████▎ | 26/49 [00:19<00:17, 1.32it/s] 55%|█████▌ | 27/49 [00:20<00:16, 1.32it/s] 57%|█████▋ | 28/49 [00:21<00:15, 1.32it/s] 59%|█████▉ | 29/49 [00:21<00:15, 1.32it/s] 61%|██████ | 30/49 [00:22<00:14, 1.32it/s] 63%|██████▎ | 31/49 [00:23<00:13, 1.32it/s] 65%|██████▌ | 32/49 [00:24<00:12, 1.32it/s] 67%|██████▋ | 33/49 [00:24<00:12, 1.32it/s] 69%|██████▉ | 34/49 [00:25<00:11, 1.32it/s] 71%|███████▏ | 35/49 [00:26<00:10, 1.32it/s] 73%|███████▎ | 36/49 [00:27<00:09, 1.32it/s] 76%|███████▌ | 37/49 [00:27<00:09, 1.32it/s] 78%|███████▊ | 38/49 [00:28<00:08, 1.32it/s] 80%|███████▉ | 39/49 [00:29<00:07, 1.32it/s] 82%|████████▏ | 40/49 [00:30<00:06, 1.32it/s] 84%|████████▎ | 41/49 [00:30<00:06, 1.32it/s] 86%|████████▌ | 42/49 [00:31<00:05, 1.32it/s] 88%|████████▊ | 43/49 [00:32<00:04, 1.32it/s] 90%|████████▉ | 44/49 [00:33<00:03, 1.32it/s] 92%|█████████▏| 45/49 [00:33<00:03, 1.32it/s] 94%|█████████▍| 46/49 [00:34<00:02, 1.32it/s] 96%|█████████▌| 47/49 [00:35<00:01, 1.32it/s] 98%|█████████▊| 48/49 [00:36<00:00, 1.32it/s] 100%|██████████| 49/49 [00:37<00:00, 1.32it/s] 100%|██████████| 49/49 [00:37<00:00, 1.32it/s]Prediction
igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28IDrd0jrk5tzsrm20chjfgte6fg8rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- painting of snowy mountain, 360 view, in the style of TOK
- lora_scale
- 1
- num_outputs
- 3
- aspect_ratio
- 16:9
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 49
{ "model": "dev", "prompt": "painting of snowy mountain, 360 view, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 }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 igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28", { input: { model: "dev", prompt: "painting of snowy mountain, 360 view, in the style of TOK", lora_scale: 1, num_outputs: 3, aspect_ratio: "16:9", output_format: "png", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 49 } } ); // 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 igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28", input={ "model": "dev", "prompt": "painting of snowy mountain, 360 view, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run igorriti/flux-360 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": "igorriti/flux-360:6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28", "input": { "model": "dev", "prompt": "painting of snowy mountain, 360 view, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-27T12:50:08.719777Z", "created_at": "2024-08-27T12:48:49.918000Z", "data_removed": false, "error": null, "id": "rd0jrk5tzsrm20chjfgte6fg8r", "input": { "model": "dev", "prompt": "painting of snowy mountain, 360 view, in the style of TOK", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 49 }, "logs": "Using seed: 41458\nPrompt: painting of snowy mountain, 360 view, in the style of TOK\ntxt2img mode\nUsing dev model\nfree=9828756942848\nDownloading weights\n2024-08-27T12:48:50Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpw9egerx6/weights url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar\n2024-08-27T12:48:51Z | INFO | [ Complete ] dest=/tmp/tmpw9egerx6/weights size=\"172 MB\" total_elapsed=1.050s url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar\nDownloaded weights in 1.14s\nLoaded LoRAs in 39.58s\n 0%| | 0/49 [00:00<?, ?it/s]\n 2%|▏ | 1/49 [00:00<00:35, 1.34it/s]\n 4%|▍ | 2/49 [00:01<00:30, 1.53it/s]\n 6%|▌ | 3/49 [00:02<00:32, 1.43it/s]\n 8%|▊ | 4/49 [00:02<00:32, 1.39it/s]\n 10%|█ | 5/49 [00:03<00:32, 1.36it/s]\n 12%|█▏ | 6/49 [00:04<00:31, 1.35it/s]\n 14%|█▍ | 7/49 [00:05<00:31, 1.34it/s]\n 16%|█▋ | 8/49 [00:05<00:30, 1.33it/s]\n 18%|█▊ | 9/49 [00:06<00:30, 1.33it/s]\n 20%|██ | 10/49 [00:07<00:29, 1.33it/s]\n 22%|██▏ | 11/49 [00:08<00:28, 1.33it/s]\n 24%|██▍ | 12/49 [00:08<00:27, 1.33it/s]\n 27%|██▋ | 13/49 [00:09<00:27, 1.32it/s]\n 29%|██▊ | 14/49 [00:10<00:26, 1.33it/s]\n 31%|███ | 15/49 [00:11<00:25, 1.32it/s]\n 33%|███▎ | 16/49 [00:11<00:24, 1.32it/s]\n 35%|███▍ | 17/49 [00:12<00:24, 1.32it/s]\n 37%|███▋ | 18/49 [00:13<00:23, 1.32it/s]\n 39%|███▉ | 19/49 [00:14<00:22, 1.32it/s]\n 41%|████ | 20/49 [00:14<00:21, 1.32it/s]\n 43%|████▎ | 21/49 [00:15<00:21, 1.32it/s]\n 45%|████▍ | 22/49 [00:16<00:20, 1.32it/s]\n 47%|████▋ | 23/49 [00:17<00:19, 1.32it/s]\n 49%|████▉ | 24/49 [00:17<00:18, 1.32it/s]\n 51%|█████ | 25/49 [00:18<00:18, 1.32it/s]\n 53%|█████▎ | 26/49 [00:19<00:17, 1.32it/s]\n 55%|█████▌ | 27/49 [00:20<00:16, 1.32it/s]\n 57%|█████▋ | 28/49 [00:20<00:15, 1.32it/s]\n 59%|█████▉ | 29/49 [00:21<00:15, 1.32it/s]\n 61%|██████ | 30/49 [00:22<00:14, 1.32it/s]\n 63%|██████▎ | 31/49 [00:23<00:13, 1.32it/s]\n 65%|██████▌ | 32/49 [00:24<00:12, 1.32it/s]\n 67%|██████▋ | 33/49 [00:24<00:12, 1.32it/s]\n 69%|██████▉ | 34/49 [00:25<00:11, 1.32it/s]\n 71%|███████▏ | 35/49 [00:26<00:10, 1.32it/s]\n 73%|███████▎ | 36/49 [00:27<00:09, 1.32it/s]\n 76%|███████▌ | 37/49 [00:27<00:09, 1.32it/s]\n 78%|███████▊ | 38/49 [00:28<00:08, 1.32it/s]\n 80%|███████▉ | 39/49 [00:29<00:07, 1.32it/s]\n 82%|████████▏ | 40/49 [00:30<00:06, 1.32it/s]\n 84%|████████▎ | 41/49 [00:30<00:06, 1.32it/s]\n 86%|████████▌ | 42/49 [00:31<00:05, 1.32it/s]\n 88%|████████▊ | 43/49 [00:32<00:04, 1.32it/s]\n 90%|████████▉ | 44/49 [00:33<00:03, 1.32it/s]\n 92%|█████████▏| 45/49 [00:33<00:03, 1.32it/s]\n 94%|█████████▍| 46/49 [00:34<00:02, 1.32it/s]\n 96%|█████████▌| 47/49 [00:35<00:01, 1.32it/s]\n 98%|█████████▊| 48/49 [00:36<00:00, 1.32it/s]\n100%|██████████| 49/49 [00:36<00:00, 1.32it/s]\n100%|██████████| 49/49 [00:36<00:00, 1.33it/s]", "metrics": { "predict_time": 78.790543058, "total_time": 78.801777 }, "output": [ "https://replicate.delivery/yhqm/Ke5crR7exsqo20evoI8cfeBpVRfrI1YQuJIFRV4fnNIKA7brJA/out-0.png", "https://replicate.delivery/yhqm/m0Vfkg6eaWrt7kbbWuhWV3voyAb38DzjuoG8WKo8TvJA23WTA/out-1.png", "https://replicate.delivery/yhqm/SftTnwLeGSqHA0P1O7B0HPoyn77fNPAWe0IYxHQxXTGCYf2aC/out-2.png" ], "started_at": "2024-08-27T12:48:49.929234Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/rd0jrk5tzsrm20chjfgte6fg8r", "cancel": "https://api.replicate.com/v1/predictions/rd0jrk5tzsrm20chjfgte6fg8r/cancel" }, "version": "6cabf39640b73eaa4af6ea3032cde29699849419271a0895f17ac81bc70d5a28" }Generated inUsing seed: 41458 Prompt: painting of snowy mountain, 360 view, in the style of TOK txt2img mode Using dev model free=9828756942848 Downloading weights 2024-08-27T12:48:50Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpw9egerx6/weights url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar 2024-08-27T12:48:51Z | INFO | [ Complete ] dest=/tmp/tmpw9egerx6/weights size="172 MB" total_elapsed=1.050s url=https://replicate.delivery/yhqm/WROeFNEXMhWrLygenOiCrQ5DO04uMvJxrksUFe1Xpt5cCUtmA/trained_model.tar Downloaded weights in 1.14s Loaded LoRAs in 39.58s 0%| | 0/49 [00:00<?, ?it/s] 2%|▏ | 1/49 [00:00<00:35, 1.34it/s] 4%|▍ | 2/49 [00:01<00:30, 1.53it/s] 6%|▌ | 3/49 [00:02<00:32, 1.43it/s] 8%|▊ | 4/49 [00:02<00:32, 1.39it/s] 10%|█ | 5/49 [00:03<00:32, 1.36it/s] 12%|█▏ | 6/49 [00:04<00:31, 1.35it/s] 14%|█▍ | 7/49 [00:05<00:31, 1.34it/s] 16%|█▋ | 8/49 [00:05<00:30, 1.33it/s] 18%|█▊ | 9/49 [00:06<00:30, 1.33it/s] 20%|██ | 10/49 [00:07<00:29, 1.33it/s] 22%|██▏ | 11/49 [00:08<00:28, 1.33it/s] 24%|██▍ | 12/49 [00:08<00:27, 1.33it/s] 27%|██▋ | 13/49 [00:09<00:27, 1.32it/s] 29%|██▊ | 14/49 [00:10<00:26, 1.33it/s] 31%|███ | 15/49 [00:11<00:25, 1.32it/s] 33%|███▎ | 16/49 [00:11<00:24, 1.32it/s] 35%|███▍ | 17/49 [00:12<00:24, 1.32it/s] 37%|███▋ | 18/49 [00:13<00:23, 1.32it/s] 39%|███▉ | 19/49 [00:14<00:22, 1.32it/s] 41%|████ | 20/49 [00:14<00:21, 1.32it/s] 43%|████▎ | 21/49 [00:15<00:21, 1.32it/s] 45%|████▍ | 22/49 [00:16<00:20, 1.32it/s] 47%|████▋ | 23/49 [00:17<00:19, 1.32it/s] 49%|████▉ | 24/49 [00:17<00:18, 1.32it/s] 51%|█████ | 25/49 [00:18<00:18, 1.32it/s] 53%|█████▎ | 26/49 [00:19<00:17, 1.32it/s] 55%|█████▌ | 27/49 [00:20<00:16, 1.32it/s] 57%|█████▋ | 28/49 [00:20<00:15, 1.32it/s] 59%|█████▉ | 29/49 [00:21<00:15, 1.32it/s] 61%|██████ | 30/49 [00:22<00:14, 1.32it/s] 63%|██████▎ | 31/49 [00:23<00:13, 1.32it/s] 65%|██████▌ | 32/49 [00:24<00:12, 1.32it/s] 67%|██████▋ | 33/49 [00:24<00:12, 1.32it/s] 69%|██████▉ | 34/49 [00:25<00:11, 1.32it/s] 71%|███████▏ | 35/49 [00:26<00:10, 1.32it/s] 73%|███████▎ | 36/49 [00:27<00:09, 1.32it/s] 76%|███████▌ | 37/49 [00:27<00:09, 1.32it/s] 78%|███████▊ | 38/49 [00:28<00:08, 1.32it/s] 80%|███████▉ | 39/49 [00:29<00:07, 1.32it/s] 82%|████████▏ | 40/49 [00:30<00:06, 1.32it/s] 84%|████████▎ | 41/49 [00:30<00:06, 1.32it/s] 86%|████████▌ | 42/49 [00:31<00:05, 1.32it/s] 88%|████████▊ | 43/49 [00:32<00:04, 1.32it/s] 90%|████████▉ | 44/49 [00:33<00:03, 1.32it/s] 92%|█████████▏| 45/49 [00:33<00:03, 1.32it/s] 94%|█████████▍| 46/49 [00:34<00:02, 1.32it/s] 96%|█████████▌| 47/49 [00:35<00:01, 1.32it/s] 98%|█████████▊| 48/49 [00:36<00:00, 1.32it/s] 100%|██████████| 49/49 [00:36<00:00, 1.32it/s] 100%|██████████| 49/49 [00:36<00:00, 1.33it/s]Prediction
igorriti/flux-360:7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211eIDxpbqrwwk3hrm60chk638ny9jprStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a snowy mountain, 360 view in the style of TOK
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a snowy mountain, 360 view in the style of TOK", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "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"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "igorriti/flux-360:7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211e", { input: { model: "dev", prompt: "a snowy mountain, 360 view in the style of TOK", lora_scale: 1, num_outputs: 4, aspect_ratio: "16:9", output_format: "webp", 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 igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "igorriti/flux-360:7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211e", input={ "model": "dev", "prompt": "a snowy mountain, 360 view in the style of TOK", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run igorriti/flux-360 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": "igorriti/flux-360:7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211e", "input": { "model": "dev", "prompt": "a snowy mountain, 360 view in the style of TOK", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "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": "2024-08-28T15:07:43.181132Z", "created_at": "2024-08-28T15:06:59.228000Z", "data_removed": false, "error": null, "id": "xpbqrwwk3hrm60chk638ny9jpr", "input": { "model": "dev", "prompt": "a snowy mountain, 360 view in the style of TOK", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 550\nPrompt: a snowy mountain, 360 view in the style of TOK\ntxt2img mode\nUsing dev model\nfree=9518195560448\nDownloading weights\n2024-08-28T15:06:59Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpxtgszdek/weights url=https://replicate.delivery/yhqm/JadMcXHmesynVK8UUvwBtfJbWWtg44dMcireTuH5jkXdjdumA/trained_model.tar\n2024-08-28T15:07:04Z | INFO | [ Complete ] dest=/tmp/tmpxtgszdek/weights size=\"172 MB\" total_elapsed=4.809s url=https://replicate.delivery/yhqm/JadMcXHmesynVK8UUvwBtfJbWWtg44dMcireTuH5jkXdjdumA/trained_model.tar\nDownloaded weights in 4.84s\nLoaded LoRAs in 14.45s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:26, 1.00it/s]\n 7%|▋ | 2/28 [00:01<00:22, 1.15it/s]\n 11%|█ | 3/28 [00:02<00:23, 1.07it/s]\n 14%|█▍ | 4/28 [00:03<00:23, 1.04it/s]\n 18%|█▊ | 5/28 [00:04<00:22, 1.03it/s]\n 21%|██▏ | 6/28 [00:05<00:21, 1.02it/s]\n 25%|██▌ | 7/28 [00:06<00:20, 1.01it/s]\n 29%|██▊ | 8/28 [00:07<00:19, 1.01it/s]\n 32%|███▏ | 9/28 [00:08<00:18, 1.01it/s]\n 36%|███▌ | 10/28 [00:09<00:17, 1.00it/s]\n 39%|███▉ | 11/28 [00:10<00:16, 1.00it/s]\n 43%|████▎ | 12/28 [00:11<00:15, 1.00it/s]\n 46%|████▋ | 13/28 [00:12<00:14, 1.00it/s]\n 50%|█████ | 14/28 [00:13<00:14, 1.00s/it]\n 54%|█████▎ | 15/28 [00:14<00:13, 1.00s/it]\n 57%|█████▋ | 16/28 [00:15<00:12, 1.00s/it]\n 61%|██████ | 17/28 [00:16<00:11, 1.00s/it]\n 64%|██████▍ | 18/28 [00:17<00:10, 1.00s/it]\n 68%|██████▊ | 19/28 [00:18<00:09, 1.00s/it]\n 71%|███████▏ | 20/28 [00:19<00:08, 1.00s/it]\n 75%|███████▌ | 21/28 [00:20<00:07, 1.00s/it]\n 79%|███████▊ | 22/28 [00:21<00:06, 1.00s/it]\n 82%|████████▏ | 23/28 [00:22<00:05, 1.00s/it]\n 86%|████████▌ | 24/28 [00:23<00:04, 1.00s/it]\n 89%|████████▉ | 25/28 [00:24<00:03, 1.00s/it]\n 93%|█████████▎| 26/28 [00:25<00:02, 1.00s/it]\n 96%|█████████▋| 27/28 [00:26<00:01, 1.00s/it]\n100%|██████████| 28/28 [00:27<00:00, 1.00s/it]\n100%|██████████| 28/28 [00:27<00:00, 1.01it/s]", "metrics": { "predict_time": 43.946216249, "total_time": 43.953132 }, "output": [ "https://replicate.delivery/yhqm/np3eb0GwvCw2LilPDPFlzLM0RaxpJnq4zwaBPyVKD2bf8OXTA/out-0.webp", "https://replicate.delivery/yhqm/fRufN3a8hrodEEuWfUQxyWqx8CMkQduQjanCeYTvppe1n35aC/out-1.webp", "https://replicate.delivery/yhqm/6DQH5kzeslWpDaTMW00NyblPe6yrlQh4SShIEadDp7Rf5dumA/out-2.webp", "https://replicate.delivery/yhqm/ZnJAMJn22koAHZN72yf0zFD0tf05Vqcm1At64s87IUOf5dumA/out-3.webp" ], "started_at": "2024-08-28T15:06:59.234916Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xpbqrwwk3hrm60chk638ny9jpr", "cancel": "https://api.replicate.com/v1/predictions/xpbqrwwk3hrm60chk638ny9jpr/cancel" }, "version": "7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211e" }Generated inUsing seed: 550 Prompt: a snowy mountain, 360 view in the style of TOK txt2img mode Using dev model free=9518195560448 Downloading weights 2024-08-28T15:06:59Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpxtgszdek/weights url=https://replicate.delivery/yhqm/JadMcXHmesynVK8UUvwBtfJbWWtg44dMcireTuH5jkXdjdumA/trained_model.tar 2024-08-28T15:07:04Z | INFO | [ Complete ] dest=/tmp/tmpxtgszdek/weights size="172 MB" total_elapsed=4.809s url=https://replicate.delivery/yhqm/JadMcXHmesynVK8UUvwBtfJbWWtg44dMcireTuH5jkXdjdumA/trained_model.tar Downloaded weights in 4.84s Loaded LoRAs in 14.45s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:26, 1.00it/s] 7%|▋ | 2/28 [00:01<00:22, 1.15it/s] 11%|█ | 3/28 [00:02<00:23, 1.07it/s] 14%|█▍ | 4/28 [00:03<00:23, 1.04it/s] 18%|█▊ | 5/28 [00:04<00:22, 1.03it/s] 21%|██▏ | 6/28 [00:05<00:21, 1.02it/s] 25%|██▌ | 7/28 [00:06<00:20, 1.01it/s] 29%|██▊ | 8/28 [00:07<00:19, 1.01it/s] 32%|███▏ | 9/28 [00:08<00:18, 1.01it/s] 36%|███▌ | 10/28 [00:09<00:17, 1.00it/s] 39%|███▉ | 11/28 [00:10<00:16, 1.00it/s] 43%|████▎ | 12/28 [00:11<00:15, 1.00it/s] 46%|████▋ | 13/28 [00:12<00:14, 1.00it/s] 50%|█████ | 14/28 [00:13<00:14, 1.00s/it] 54%|█████▎ | 15/28 [00:14<00:13, 1.00s/it] 57%|█████▋ | 16/28 [00:15<00:12, 1.00s/it] 61%|██████ | 17/28 [00:16<00:11, 1.00s/it] 64%|██████▍ | 18/28 [00:17<00:10, 1.00s/it] 68%|██████▊ | 19/28 [00:18<00:09, 1.00s/it] 71%|███████▏ | 20/28 [00:19<00:08, 1.00s/it] 75%|███████▌ | 21/28 [00:20<00:07, 1.00s/it] 79%|███████▊ | 22/28 [00:21<00:06, 1.00s/it] 82%|████████▏ | 23/28 [00:22<00:05, 1.00s/it] 86%|████████▌ | 24/28 [00:23<00:04, 1.00s/it] 89%|████████▉ | 25/28 [00:24<00:03, 1.00s/it] 93%|█████████▎| 26/28 [00:25<00:02, 1.00s/it] 96%|█████████▋| 27/28 [00:26<00:01, 1.00s/it] 100%|██████████| 28/28 [00:27<00:00, 1.00s/it] 100%|██████████| 28/28 [00:27<00:00, 1.01it/s]Prediction
igorriti/flux-360:7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211eID2jpf51871xrm20chk6a93vx4e8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- A vintage photo of a pirate ship navigating the sea. 360 view in the style of TOK
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "A vintage photo of a pirate ship navigating the sea. 360 view in the style of TOK", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "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"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "igorriti/flux-360:7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211e", { input: { model: "dev", prompt: "A vintage photo of a pirate ship navigating the sea. 360 view in the style of TOK", lora_scale: 1, num_outputs: 4, aspect_ratio: "16:9", output_format: "webp", 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 igorriti/flux-360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "igorriti/flux-360:7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211e", input={ "model": "dev", "prompt": "A vintage photo of a pirate ship navigating the sea. 360 view in the style of TOK", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run igorriti/flux-360 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": "igorriti/flux-360:7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211e", "input": { "model": "dev", "prompt": "A vintage photo of a pirate ship navigating the sea. 360 view in the style of TOK", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "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": "2024-08-28T15:22:25.040435Z", "created_at": "2024-08-28T15:21:40.879000Z", "data_removed": false, "error": null, "id": "2jpf51871xrm20chk6a93vx4e8", "input": { "model": "dev", "prompt": "A vintage photo of a pirate ship navigating the sea. 360 view in the style of TOK", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 47372\nPrompt: A vintage photo of a pirate ship navigating the sea. 360 view in the style of TOK\ntxt2img mode\nUsing dev model\nfree=9517699235840\nDownloading weights\n2024-08-28T15:21:45Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmphgr2gfms/weights url=https://replicate.delivery/yhqm/JadMcXHmesynVK8UUvwBtfJbWWtg44dMcireTuH5jkXdjdumA/trained_model.tar\n2024-08-28T15:21:47Z | INFO | [ Complete ] dest=/tmp/tmphgr2gfms/weights size=\"172 MB\" total_elapsed=1.425s url=https://replicate.delivery/yhqm/JadMcXHmesynVK8UUvwBtfJbWWtg44dMcireTuH5jkXdjdumA/trained_model.tar\nDownloaded weights in 1.46s\nLoaded LoRAs in 9.52s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:27, 1.02s/it]\n 7%|▋ | 2/28 [00:01<00:23, 1.13it/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, 1.01it/s]\n 21%|██▏ | 6/28 [00:05<00:21, 1.00it/s]\n 25%|██▌ | 7/28 [00:06<00:21, 1.00s/it]\n 29%|██▊ | 8/28 [00:07<00:20, 1.01s/it]\n 32%|███▏ | 9/28 [00:08<00:19, 1.01s/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 [00:14<00:14, 1.02s/it]\n 54%|█████▎ | 15/28 [00:15<00:13, 1.02s/it]\n 57%|█████▋ | 16/28 [00:16<00:12, 1.02s/it]\n 61%|██████ | 17/28 [00:17<00:11, 1.02s/it]\n 64%|██████▍ | 18/28 [00:18<00:10, 1.02s/it]\n 68%|██████▊ | 19/28 [00:19<00:09, 1.02s/it]\n 71%|███████▏ | 20/28 [00:20<00:08, 1.01s/it]\n 75%|███████▌ | 21/28 [00:21<00:07, 1.02s/it]\n 79%|███████▊ | 22/28 [00:22<00:06, 1.02s/it]\n 82%|████████▏ | 23/28 [00:23<00:05, 1.02s/it]\n 86%|████████▌ | 24/28 [00:24<00:04, 1.02s/it]\n 89%|████████▉ | 25/28 [00:25<00:03, 1.02s/it]\n 93%|█████████▎| 26/28 [00:26<00:02, 1.02s/it]\n 96%|█████████▋| 27/28 [00:27<00:01, 1.02s/it]\n100%|██████████| 28/28 [00:28<00:00, 1.02s/it]\n100%|██████████| 28/28 [00:28<00:00, 1.01s/it]", "metrics": { "predict_time": 39.388779349, "total_time": 44.161435 }, "output": [ "https://replicate.delivery/yhqm/1o7qYAmWI57edaDDyZ0GiJf9XEqpLovleraTtvUAfBXDr8cNB/out-0.webp", "https://replicate.delivery/yhqm/Vfs60NrA492TaqAKzqXekGB5bvxNbA0e48EaeVvfIT0GW55aC/out-1.webp", "https://replicate.delivery/yhqm/9KspE2MrahYpE9bBQ7mHyv3jPKE1iyzCJVYXqWXXhPGsyz1E/out-2.webp", "https://replicate.delivery/yhqm/ZQbKzNFD8jYWBlwyNtWAAVyiaH2oOZqXdoiPPnKeLdewKPXTA/out-3.webp" ], "started_at": "2024-08-28T15:21:45.651655Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/2jpf51871xrm20chk6a93vx4e8", "cancel": "https://api.replicate.com/v1/predictions/2jpf51871xrm20chk6a93vx4e8/cancel" }, "version": "7c47dae76f2ce43c09245644c4706d472655ca9736f67b0dcafb59385471211e" }Generated inUsing seed: 47372 Prompt: A vintage photo of a pirate ship navigating the sea. 360 view in the style of TOK txt2img mode Using dev model free=9517699235840 Downloading weights 2024-08-28T15:21:45Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmphgr2gfms/weights url=https://replicate.delivery/yhqm/JadMcXHmesynVK8UUvwBtfJbWWtg44dMcireTuH5jkXdjdumA/trained_model.tar 2024-08-28T15:21:47Z | INFO | [ Complete ] dest=/tmp/tmphgr2gfms/weights size="172 MB" total_elapsed=1.425s url=https://replicate.delivery/yhqm/JadMcXHmesynVK8UUvwBtfJbWWtg44dMcireTuH5jkXdjdumA/trained_model.tar Downloaded weights in 1.46s Loaded LoRAs in 9.52s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:27, 1.02s/it] 7%|▋ | 2/28 [00:01<00:23, 1.13it/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, 1.01it/s] 21%|██▏ | 6/28 [00:05<00:21, 1.00it/s] 25%|██▌ | 7/28 [00:06<00:21, 1.00s/it] 29%|██▊ | 8/28 [00:07<00:20, 1.01s/it] 32%|███▏ | 9/28 [00:08<00:19, 1.01s/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 [00:14<00:14, 1.02s/it] 54%|█████▎ | 15/28 [00:15<00:13, 1.02s/it] 57%|█████▋ | 16/28 [00:16<00:12, 1.02s/it] 61%|██████ | 17/28 [00:17<00:11, 1.02s/it] 64%|██████▍ | 18/28 [00:18<00:10, 1.02s/it] 68%|██████▊ | 19/28 [00:19<00:09, 1.02s/it] 71%|███████▏ | 20/28 [00:20<00:08, 1.01s/it] 75%|███████▌ | 21/28 [00:21<00:07, 1.02s/it] 79%|███████▊ | 22/28 [00:22<00:06, 1.02s/it] 82%|████████▏ | 23/28 [00:23<00:05, 1.02s/it] 86%|████████▌ | 24/28 [00:24<00:04, 1.02s/it] 89%|████████▉ | 25/28 [00:25<00:03, 1.02s/it] 93%|█████████▎| 26/28 [00:26<00:02, 1.02s/it] 96%|█████████▋| 27/28 [00:27<00:01, 1.02s/it] 100%|██████████| 28/28 [00:28<00:00, 1.02s/it] 100%|██████████| 28/28 [00:28<00:00, 1.01s/it]
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