aramintak
/
flux-frosting-lane
Flux lora, use "frstingln illustration" to trigger the image generation
- Public
- 1.2K runs
-
H100
- Paper
Prediction
aramintak/flux-frosting-lane:04612fc7f01c413d33337bdd0df4a471f13397101015067e24e148dd5f2d5c2fIDmxwezm92s1rm60chc15bcfdbzmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a pink crystal gem suspended in space, frstingln illustration
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a pink crystal gem suspended in space, frstingln illustration", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/flux-frosting-lane using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/flux-frosting-lane:04612fc7f01c413d33337bdd0df4a471f13397101015067e24e148dd5f2d5c2f", { input: { model: "dev", prompt: "a pink crystal gem suspended in space, frstingln illustration", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/flux-frosting-lane using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/flux-frosting-lane:04612fc7f01c413d33337bdd0df4a471f13397101015067e24e148dd5f2d5c2f", input={ "model": "dev", "prompt": "a pink crystal gem suspended in space, frstingln illustration", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run aramintak/flux-frosting-lane 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": "aramintak/flux-frosting-lane:04612fc7f01c413d33337bdd0df4a471f13397101015067e24e148dd5f2d5c2f", "input": { "model": "dev", "prompt": "a pink crystal gem suspended in space, frstingln illustration", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-17T12:22:57.193983Z", "created_at": "2024-08-17T12:22:37Z", "data_removed": false, "error": null, "id": "mxwezm92s1rm60chc15bcfdbzm", "input": { "model": "dev", "prompt": "a pink crystal gem suspended in space, frstingln illustration", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 63485\nPrompt: a pink crystal gem suspended in space, frstingln illustration\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9717446037504\nDownloading weights\n2024-08-17T12:22:39Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/c7c036606be7034b url=https://replicate.delivery/yhqm/kz0eJkWNfmirRUqGcIZMxankUbYJHdnZDVQFEz1xeeok9RONB/trained_model.tar\n2024-08-17T12:22:40Z | INFO | [ Complete ] dest=/src/weights-cache/c7c036606be7034b size=\"172 MB\" total_elapsed=1.213s url=https://replicate.delivery/yhqm/kz0eJkWNfmirRUqGcIZMxankUbYJHdnZDVQFEz1xeeok9RONB/trained_model.tar\nb''\nDownloaded weights in 1.2420926094055176 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.65it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.21it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.95it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.83it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.76it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.72it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.67it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.66it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.67it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.67it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.66it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.66it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.67it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.67it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]", "metrics": { "predict_time": 17.879904906, "total_time": 20.193983 }, "output": [ "https://replicate.delivery/yhqm/DzN4bMHcNJY7H1JKtWT4I7XSqfFdatPU9vRcfKHIDYphgkTTA/out-0.webp" ], "started_at": "2024-08-17T12:22:39.314079Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/mxwezm92s1rm60chc15bcfdbzm", "cancel": "https://api.replicate.com/v1/predictions/mxwezm92s1rm60chc15bcfdbzm/cancel" }, "version": "04612fc7f01c413d33337bdd0df4a471f13397101015067e24e148dd5f2d5c2f" }Generated inUsing seed: 63485 Prompt: a pink crystal gem suspended in space, frstingln illustration txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9717446037504 Downloading weights 2024-08-17T12:22:39Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/c7c036606be7034b url=https://replicate.delivery/yhqm/kz0eJkWNfmirRUqGcIZMxankUbYJHdnZDVQFEz1xeeok9RONB/trained_model.tar 2024-08-17T12:22:40Z | INFO | [ Complete ] dest=/src/weights-cache/c7c036606be7034b size="172 MB" total_elapsed=1.213s url=https://replicate.delivery/yhqm/kz0eJkWNfmirRUqGcIZMxankUbYJHdnZDVQFEz1xeeok9RONB/trained_model.tar b'' Downloaded weights in 1.2420926094055176 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.65it/s] 7%|▋ | 2/28 [00:00<00:06, 4.21it/s] 11%|█ | 3/28 [00:00<00:06, 3.95it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.83it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.76it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.72it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.67it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.66it/s] 50%|█████ | 14/28 [00:03<00:03, 3.67it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.67it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s] 61%|██████ | 17/28 [00:04<00:03, 3.66it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.66it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.67it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.67it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s]Prediction
aramintak/flux-frosting-lane:04612fc7f01c413d33337bdd0df4a471f13397101015067e24e148dd5f2d5c2fID9wm9g54tk5rm20chc15vpc4cbgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a beautiful castle frstingln illustration
- lora_scale
- 0.75
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a beautiful castle frstingln illustration", "lora_scale": 0.75, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/flux-frosting-lane using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/flux-frosting-lane:04612fc7f01c413d33337bdd0df4a471f13397101015067e24e148dd5f2d5c2f", { input: { model: "dev", prompt: "a beautiful castle frstingln illustration", lora_scale: 0.75, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/flux-frosting-lane using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/flux-frosting-lane:04612fc7f01c413d33337bdd0df4a471f13397101015067e24e148dd5f2d5c2f", input={ "model": "dev", "prompt": "a beautiful castle frstingln illustration", "lora_scale": 0.75, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run aramintak/flux-frosting-lane 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": "aramintak/flux-frosting-lane:04612fc7f01c413d33337bdd0df4a471f13397101015067e24e148dd5f2d5c2f", "input": { "model": "dev", "prompt": "a beautiful castle frstingln illustration", "lora_scale": 0.75, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-17T12:24:52.450392Z", "created_at": "2024-08-17T12:24:13.209000Z", "data_removed": false, "error": null, "id": "9wm9g54tk5rm20chc15vpc4cbg", "input": { "model": "dev", "prompt": "a beautiful castle frstingln illustration", "lora_scale": 0.75, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 23142\nPrompt: a beautiful castle frstingln illustration\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nweights already loaded!\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.51it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.93it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.74it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.66it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.62it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.59it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.57it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.57it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.56it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.55it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.54it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.54it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.54it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.54it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.54it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.54it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.54it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.54it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.54it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.54it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.54it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.54it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.54it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.54it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.54it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.54it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.53it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.54it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.56it/s]", "metrics": { "predict_time": 8.436877046, "total_time": 39.241392 }, "output": [ "https://replicate.delivery/yhqm/9q9yJT08SGJEHxjz0korldw6FpPRPBzCrSqeK1p5GoMKRypJA/out-0.webp" ], "started_at": "2024-08-17T12:24:44.013515Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/9wm9g54tk5rm20chc15vpc4cbg", "cancel": "https://api.replicate.com/v1/predictions/9wm9g54tk5rm20chc15vpc4cbg/cancel" }, "version": "04612fc7f01c413d33337bdd0df4a471f13397101015067e24e148dd5f2d5c2f" }Generated inUsing seed: 23142 Prompt: a beautiful castle frstingln illustration txt2img mode Using dev model Loading LoRA weights weights already loaded! 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.51it/s] 7%|▋ | 2/28 [00:00<00:06, 3.93it/s] 11%|█ | 3/28 [00:00<00:06, 3.74it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.66it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.62it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.59it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.57it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.57it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.56it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.55it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.54it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.54it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.54it/s] 50%|█████ | 14/28 [00:03<00:03, 3.54it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.54it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.54it/s] 61%|██████ | 17/28 [00:04<00:03, 3.54it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.54it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.54it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.54it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.54it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.54it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.54it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.54it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.54it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.54it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.53it/s] 100%|██████████| 28/28 [00:07<00:00, 3.54it/s] 100%|██████████| 28/28 [00:07<00:00, 3.56it/s]
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