aleksa-codes
/
flux-ghibsky-illustration
Flux LoRA, use 'GHIBSKY style' to trigger generation, creates serene and enchanting landscapes with vibrant, surreal skies and intricate, Ghibli-inspired elements reminiscent of the atmospheric beauty found in Makoto Shinkai's works
- Public
- 76.2K runs
-
H100
- Weights
Prediction
aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0IDp6amm8xwz9rm00che2rtkya19rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 9:16
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 28
{ "model": "dev", "prompt": "GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", { input: { model: "dev", prompt: "GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights", lora_scale: 1, num_outputs: 1, aspect_ratio: "9:16", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, 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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", input={ "model": "dev", "prompt": "GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run aleksa-codes/flux-ghibsky-illustration 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": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", "input": { "model": "dev", "prompt": "GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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": "2024-08-20T16:50:00.663575Z", "created_at": "2024-08-20T16:49:42.138000Z", "data_removed": false, "error": null, "id": "p6amm8xwz9rm00che2rtkya19r", "input": { "model": "dev", "prompt": "GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 }, "logs": "Using seed: 64884\nPrompt: GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.70it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.97it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.76it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.70it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.70it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.70it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.70it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.69it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.70it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.70it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.69it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.69it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.69it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.69it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.72it/s]", "metrics": { "predict_time": 17.565027229000002, "total_time": 18.525575 }, "output": [ "https://replicate.delivery/yhqm/9Z9n5qPvKDonG5057ESfBGDisxdVAG0dfPKRRHAieD3wZPpmA/out-0.jpg" ], "started_at": "2024-08-20T16:49:43.098548Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/p6amm8xwz9rm00che2rtkya19r", "cancel": "https://api.replicate.com/v1/predictions/p6amm8xwz9rm00che2rtkya19r/cancel" }, "version": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0" }Generated inUsing seed: 64884 Prompt: GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.70it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.97it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.76it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.70it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.70it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.70it/s] 50%|█████ | 14/28 [00:03<00:03, 3.70it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.69it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s] 61%|██████ | 17/28 [00:04<00:02, 3.70it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.70it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.69it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.69it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.69it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.69it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s] 100%|██████████| 28/28 [00:07<00:00, 3.72it/s]Prediction
aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0IDv8k5yb3fenrm00che2t84ywmf8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- GHIBSKY style, a fisherman casting a line into a peaceful village lake surrounded by quaint cottages
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 9:16
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 28
{ "model": "dev", "prompt": "GHIBSKY style, a fisherman casting a line into a peaceful village lake surrounded by quaint cottages", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", { input: { model: "dev", prompt: "GHIBSKY style, a fisherman casting a line into a peaceful village lake surrounded by quaint cottages", lora_scale: 1, num_outputs: 1, aspect_ratio: "9:16", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, 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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", input={ "model": "dev", "prompt": "GHIBSKY style, a fisherman casting a line into a peaceful village lake surrounded by quaint cottages", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run aleksa-codes/flux-ghibsky-illustration 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": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", "input": { "model": "dev", "prompt": "GHIBSKY style, a fisherman casting a line into a peaceful village lake surrounded by quaint cottages", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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": "2024-08-20T16:52:58.925995Z", "created_at": "2024-08-20T16:52:38.901000Z", "data_removed": false, "error": null, "id": "v8k5yb3fenrm00che2t84ywmf8", "input": { "model": "dev", "prompt": "GHIBSKY style, a fisherman casting a line into a peaceful village lake surrounded by quaint cottages", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 }, "logs": "Using seed: 64165\nPrompt: GHIBSKY style, a fisherman casting a line into a peaceful village lake surrounded by quaint cottages\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.69it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.96it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.72it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.68it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.67it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.67it/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, 3.67it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/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, 3.67it/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, 3.70it/s]", "metrics": { "predict_time": 15.577594326, "total_time": 20.024995 }, "output": [ "https://replicate.delivery/yhqm/3POZ2cWPdKZgK1kLWrWngMbqG4duUXSzhuY9Ef301jD13TqJA/out-0.jpg" ], "started_at": "2024-08-20T16:52:43.348400Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/v8k5yb3fenrm00che2t84ywmf8", "cancel": "https://api.replicate.com/v1/predictions/v8k5yb3fenrm00che2t84ywmf8/cancel" }, "version": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0" }Generated inUsing seed: 64165 Prompt: GHIBSKY style, a fisherman casting a line into a peaceful village lake surrounded by quaint cottages txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.69it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.96it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.72it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s] 50%|█████ | 14/28 [00:03<00:03, 3.68it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.67it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s] 61%|██████ | 17/28 [00:04<00:02, 3.67it/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, 3.67it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/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, 3.67it/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, 3.70it/s]Prediction
aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0IDvr9g3hh1t5rm00che2xabmbr60StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- GHIBSKY style, cozy mountain cabin covered in snow, with smoke curling from the chimney and a warm, inviting light spilling through the windows
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 9:16
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 28
{ "model": "dev", "prompt": "GHIBSKY style, cozy mountain cabin covered in snow, with smoke curling from the chimney and a warm, inviting light spilling through the windows", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", { input: { model: "dev", prompt: "GHIBSKY style, cozy mountain cabin covered in snow, with smoke curling from the chimney and a warm, inviting light spilling through the windows", lora_scale: 1, num_outputs: 1, aspect_ratio: "9:16", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, 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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", input={ "model": "dev", "prompt": "GHIBSKY style, cozy mountain cabin covered in snow, with smoke curling from the chimney and a warm, inviting light spilling through the windows", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run aleksa-codes/flux-ghibsky-illustration 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": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", "input": { "model": "dev", "prompt": "GHIBSKY style, cozy mountain cabin covered in snow, with smoke curling from the chimney and a warm, inviting light spilling through the windows", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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": "2024-08-20T16:59:08.114715Z", "created_at": "2024-08-20T16:58:52.241000Z", "data_removed": false, "error": null, "id": "vr9g3hh1t5rm00che2xabmbr60", "input": { "model": "dev", "prompt": "GHIBSKY style, cozy mountain cabin covered in snow, with smoke curling from the chimney and a warm, inviting light spilling through the windows", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 }, "logs": "Using seed: 20256\nPrompt: GHIBSKY style, cozy mountain cabin covered in snow, with smoke curling from the chimney and a warm, inviting light spilling through the windows\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.68it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.95it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.83it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.70it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.69it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.67it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.66it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.66it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.66it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.66it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.65it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.65it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.65it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.65it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.65it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.65it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.66it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.65it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.65it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.65it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.65it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.65it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.65it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.68it/s]", "metrics": { "predict_time": 15.508473718, "total_time": 15.873715 }, "output": [ "https://replicate.delivery/yhqm/cHMnTe9Qd7RyFahHqOSufgh9vbAYI9w0yVyqzZKtTFGb1nUTA/out-0.jpg" ], "started_at": "2024-08-20T16:58:52.606241Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vr9g3hh1t5rm00che2xabmbr60", "cancel": "https://api.replicate.com/v1/predictions/vr9g3hh1t5rm00che2xabmbr60/cancel" }, "version": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0" }Generated inUsing seed: 20256 Prompt: GHIBSKY style, cozy mountain cabin covered in snow, with smoke curling from the chimney and a warm, inviting light spilling through the windows txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.68it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.95it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.83it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.70it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.69it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.67it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.66it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.66it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.66it/s] 50%|█████ | 14/28 [00:03<00:03, 3.66it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.65it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.65it/s] 61%|██████ | 17/28 [00:04<00:03, 3.65it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.65it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.65it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.65it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.66it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.65it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.65it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.65it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.65it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.65it/s] 100%|██████████| 28/28 [00:07<00:00, 3.65it/s] 100%|██████████| 28/28 [00:07<00:00, 3.68it/s]Prediction
aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0ID3nanndy7mdrm20che2ybp8bcncStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- height
- 1440
- prompt
- GHIBSKY style, serene Japanese garden with a koi pond and a traditional tea house, nestled under a canopy of cherry blossoms in full bloom
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- custom
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "height": 1440, "prompt": "GHIBSKY style, serene Japanese garden with a koi pond and a traditional tea house, nestled under a canopy of cherry blossoms in full bloom", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "custom", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", { input: { model: "dev", width: 1440, height: 1440, prompt: "GHIBSKY style, serene Japanese garden with a koi pond and a traditional tea house, nestled under a canopy of cherry blossoms in full bloom", lora_scale: 1, num_outputs: 1, aspect_ratio: "custom", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, 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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", input={ "model": "dev", "width": 1440, "height": 1440, "prompt": "GHIBSKY style, serene Japanese garden with a koi pond and a traditional tea house, nestled under a canopy of cherry blossoms in full bloom", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "custom", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run aleksa-codes/flux-ghibsky-illustration 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": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", "input": { "model": "dev", "width": 1440, "height": 1440, "prompt": "GHIBSKY style, serene Japanese garden with a koi pond and a traditional tea house, nestled under a canopy of cherry blossoms in full bloom", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "custom", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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": "2024-08-20T17:02:12.881920Z", "created_at": "2024-08-20T17:01:45.763000Z", "data_removed": false, "error": null, "id": "3nanndy7mdrm20che2ybp8bcnc", "input": { "model": "dev", "width": 1440, "height": 1440, "prompt": "GHIBSKY style, serene Japanese garden with a koi pond and a traditional tea house, nestled under a canopy of cherry blossoms in full bloom", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "custom", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 }, "logs": "Using seed: 55396\nPrompt: GHIBSKY style, serene Japanese garden with a koi pond and a traditional tea house, nestled under a canopy of cherry blossoms in full bloom\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:15, 1.80it/s]\n 7%|▋ | 2/28 [00:00<00:12, 2.05it/s]\n 11%|█ | 3/28 [00:01<00:13, 1.92it/s]\n 14%|█▍ | 4/28 [00:02<00:12, 1.85it/s]\n 18%|█▊ | 5/28 [00:02<00:12, 1.83it/s]\n 21%|██▏ | 6/28 [00:03<00:12, 1.81it/s]\n 25%|██▌ | 7/28 [00:03<00:11, 1.80it/s]\n 29%|██▊ | 8/28 [00:04<00:11, 1.79it/s]\n 32%|███▏ | 9/28 [00:04<00:10, 1.78it/s]\n 36%|███▌ | 10/28 [00:05<00:10, 1.78it/s]\n 39%|███▉ | 11/28 [00:06<00:09, 1.78it/s]\n 43%|████▎ | 12/28 [00:06<00:08, 1.78it/s]\n 46%|████▋ | 13/28 [00:07<00:08, 1.78it/s]\n 50%|█████ | 14/28 [00:07<00:07, 1.77it/s]\n 54%|█████▎ | 15/28 [00:08<00:07, 1.77it/s]\n 57%|█████▋ | 16/28 [00:08<00:06, 1.77it/s]\n 61%|██████ | 17/28 [00:09<00:06, 1.77it/s]\n 64%|██████▍ | 18/28 [00:10<00:05, 1.78it/s]\n 68%|██████▊ | 19/28 [00:10<00:05, 1.77it/s]\n 71%|███████▏ | 20/28 [00:11<00:04, 1.77it/s]\n 75%|███████▌ | 21/28 [00:11<00:03, 1.77it/s]\n 79%|███████▊ | 22/28 [00:12<00:03, 1.77it/s]\n 82%|████████▏ | 23/28 [00:12<00:02, 1.77it/s]\n 86%|████████▌ | 24/28 [00:13<00:02, 1.77it/s]\n 89%|████████▉ | 25/28 [00:13<00:01, 1.77it/s]\n 93%|█████████▎| 26/28 [00:14<00:01, 1.77it/s]\n 96%|█████████▋| 27/28 [00:15<00:00, 1.77it/s]\n100%|██████████| 28/28 [00:15<00:00, 1.77it/s]\n100%|██████████| 28/28 [00:15<00:00, 1.79it/s]", "metrics": { "predict_time": 23.596157145, "total_time": 27.11892 }, "output": [ "https://replicate.delivery/yhqm/woykPHLOWorvBFhgyUhVriwu1sPGOhuvNSwd2dy3xpMFeTqJA/out-0.jpg" ], "started_at": "2024-08-20T17:01:49.285763Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3nanndy7mdrm20che2ybp8bcnc", "cancel": "https://api.replicate.com/v1/predictions/3nanndy7mdrm20che2ybp8bcnc/cancel" }, "version": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0" }Generated inUsing seed: 55396 Prompt: GHIBSKY style, serene Japanese garden with a koi pond and a traditional tea house, nestled under a canopy of cherry blossoms in full bloom txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:15, 1.80it/s] 7%|▋ | 2/28 [00:00<00:12, 2.05it/s] 11%|█ | 3/28 [00:01<00:13, 1.92it/s] 14%|█▍ | 4/28 [00:02<00:12, 1.85it/s] 18%|█▊ | 5/28 [00:02<00:12, 1.83it/s] 21%|██▏ | 6/28 [00:03<00:12, 1.81it/s] 25%|██▌ | 7/28 [00:03<00:11, 1.80it/s] 29%|██▊ | 8/28 [00:04<00:11, 1.79it/s] 32%|███▏ | 9/28 [00:04<00:10, 1.78it/s] 36%|███▌ | 10/28 [00:05<00:10, 1.78it/s] 39%|███▉ | 11/28 [00:06<00:09, 1.78it/s] 43%|████▎ | 12/28 [00:06<00:08, 1.78it/s] 46%|████▋ | 13/28 [00:07<00:08, 1.78it/s] 50%|█████ | 14/28 [00:07<00:07, 1.77it/s] 54%|█████▎ | 15/28 [00:08<00:07, 1.77it/s] 57%|█████▋ | 16/28 [00:08<00:06, 1.77it/s] 61%|██████ | 17/28 [00:09<00:06, 1.77it/s] 64%|██████▍ | 18/28 [00:10<00:05, 1.78it/s] 68%|██████▊ | 19/28 [00:10<00:05, 1.77it/s] 71%|███████▏ | 20/28 [00:11<00:04, 1.77it/s] 75%|███████▌ | 21/28 [00:11<00:03, 1.77it/s] 79%|███████▊ | 22/28 [00:12<00:03, 1.77it/s] 82%|████████▏ | 23/28 [00:12<00:02, 1.77it/s] 86%|████████▌ | 24/28 [00:13<00:02, 1.77it/s] 89%|████████▉ | 25/28 [00:13<00:01, 1.77it/s] 93%|█████████▎| 26/28 [00:14<00:01, 1.77it/s] 96%|█████████▋| 27/28 [00:15<00:00, 1.77it/s] 100%|██████████| 28/28 [00:15<00:00, 1.77it/s] 100%|██████████| 28/28 [00:15<00:00, 1.79it/s]Prediction
aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0IDb8eeqy4qbhrm00che31a1znv7cStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- GHIBSKY style, a small Yorkie on a windowsill during a snowy winter night, with a warm, cozy glow from inside and soft snowflakes drifting outside
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 9:16
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 28
{ "model": "dev", "prompt": "GHIBSKY style, a small Yorkie on a windowsill during a snowy winter night, with a warm, cozy glow from inside and soft snowflakes drifting outside", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", { input: { model: "dev", prompt: "GHIBSKY style, a small Yorkie on a windowsill during a snowy winter night, with a warm, cozy glow from inside and soft snowflakes drifting outside", lora_scale: 1, num_outputs: 1, aspect_ratio: "9:16", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, 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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", input={ "model": "dev", "prompt": "GHIBSKY style, a small Yorkie on a windowsill during a snowy winter night, with a warm, cozy glow from inside and soft snowflakes drifting outside", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run aleksa-codes/flux-ghibsky-illustration 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": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", "input": { "model": "dev", "prompt": "GHIBSKY style, a small Yorkie on a windowsill during a snowy winter night, with a warm, cozy glow from inside and soft snowflakes drifting outside", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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": "2024-08-20T17:08:29.986523Z", "created_at": "2024-08-20T17:08:06.620000Z", "data_removed": false, "error": null, "id": "b8eeqy4qbhrm00che31a1znv7c", "input": { "model": "dev", "prompt": "GHIBSKY style, a small Yorkie on a windowsill during a snowy winter night, with a warm, cozy glow from inside and soft snowflakes drifting outside", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 }, "logs": "Using seed: 22552\nPrompt: GHIBSKY style, a small Yorkie on a windowsill during a snowy winter night, with a warm, cozy glow from inside and soft snowflakes drifting outside\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.69it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.96it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.72it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.68it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.68it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.67it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/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, 3.70it/s]", "metrics": { "predict_time": 16.76024557, "total_time": 23.366523 }, "output": [ "https://replicate.delivery/yhqm/MfWxBdyIKvxLcqztplNjZdjBjhIL9CqfU6BlsVVXgW1NePpmA/out-0.jpg" ], "started_at": "2024-08-20T17:08:13.226277Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/b8eeqy4qbhrm00che31a1znv7c", "cancel": "https://api.replicate.com/v1/predictions/b8eeqy4qbhrm00che31a1znv7c/cancel" }, "version": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0" }Generated inUsing seed: 22552 Prompt: GHIBSKY style, a small Yorkie on a windowsill during a snowy winter night, with a warm, cozy glow from inside and soft snowflakes drifting outside txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.69it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.96it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.72it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s] 50%|█████ | 14/28 [00:03<00:03, 3.68it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s] 61%|██████ | 17/28 [00:04<00:02, 3.68it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.67it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/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, 3.70it/s]Prediction
aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0ID5ek00q45k5rm20che3jvnnfb10StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- GHIBSKY style, Mykonos
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 9:16
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 28
{ "model": "dev", "prompt": "GHIBSKY style, Mykonos", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", { input: { model: "dev", prompt: "GHIBSKY style, Mykonos", lora_scale: 1, num_outputs: 1, aspect_ratio: "9:16", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, 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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", input={ "model": "dev", "prompt": "GHIBSKY style, Mykonos", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run aleksa-codes/flux-ghibsky-illustration 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": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", "input": { "model": "dev", "prompt": "GHIBSKY style, Mykonos", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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": "2024-08-20T17:46:39.598675Z", "created_at": "2024-08-20T17:46:15.833000Z", "data_removed": false, "error": null, "id": "5ek00q45k5rm20che3jvnnfb10", "input": { "model": "dev", "prompt": "GHIBSKY style, Mykonos", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 }, "logs": "Using seed: 3829\nPrompt: GHIBSKY style, Mykonos\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.72it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.26it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.98it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.77it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.70it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.70it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.70it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.70it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.71it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.70it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.71it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.70it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.71it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.73it/s]", "metrics": { "predict_time": 23.54672606, "total_time": 23.765675 }, "output": [ "https://replicate.delivery/yhqm/kfzfiipElipMbEbVfn3ijAf5xesZttKuqUxZTM7geF55fQUqJA/out-0.jpg" ], "started_at": "2024-08-20T17:46:16.051949Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/5ek00q45k5rm20che3jvnnfb10", "cancel": "https://api.replicate.com/v1/predictions/5ek00q45k5rm20che3jvnnfb10/cancel" }, "version": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0" }Generated inUsing seed: 3829 Prompt: GHIBSKY style, Mykonos txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.72it/s] 7%|▋ | 2/28 [00:00<00:06, 4.26it/s] 11%|█ | 3/28 [00:00<00:06, 3.98it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.77it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.70it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.70it/s] 50%|█████ | 14/28 [00:03<00:03, 3.70it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.70it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s] 61%|██████ | 17/28 [00:04<00:02, 3.71it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.70it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.71it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.70it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.71it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.73it/s]Prediction
aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0ID5vepf09pddrm20che3r966e2d8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- GHIBSKY style, an orange Lamborghini driving down a hill road at night with a beautiful ocean view in the background, side view, no text
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 9:16
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 28
{ "model": "dev", "prompt": "GHIBSKY style, an orange Lamborghini driving down a hill road at night with a beautiful ocean view in the background, side view, no text", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", { input: { model: "dev", prompt: "GHIBSKY style, an orange Lamborghini driving down a hill road at night with a beautiful ocean view in the background, side view, no text", lora_scale: 1, num_outputs: 1, aspect_ratio: "9:16", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, 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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", input={ "model": "dev", "prompt": "GHIBSKY style, an orange Lamborghini driving down a hill road at night with a beautiful ocean view in the background, side view, no text", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run aleksa-codes/flux-ghibsky-illustration 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": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", "input": { "model": "dev", "prompt": "GHIBSKY style, an orange Lamborghini driving down a hill road at night with a beautiful ocean view in the background, side view, no text", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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": "2024-08-20T17:58:18.067818Z", "created_at": "2024-08-20T17:57:56.459000Z", "data_removed": false, "error": null, "id": "5vepf09pddrm20che3r966e2d8", "input": { "model": "dev", "prompt": "GHIBSKY style, an orange Lamborghini driving down a hill road at night with a beautiful ocean view in the background, side view, no text", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 }, "logs": "Using seed: 916\nPrompt: GHIBSKY style, an orange Lamborghini driving down a hill road at night with a beautiful ocean view in the background, side view, no text\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.70it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.26it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.00it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.89it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.82it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.76it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.75it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.74it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.73it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.73it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.73it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.72it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.72it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.72it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.72it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.71it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.72it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.72it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.72it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.72it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.72it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.74it/s]", "metrics": { "predict_time": 17.367311642, "total_time": 21.608818 }, "output": [ "https://replicate.delivery/yhqm/uoedLAu4X0wlOCrpJm5Qe4s7yXSnK07eonuBm33LjRuyZRpmA/out-0.jpg" ], "started_at": "2024-08-20T17:58:00.700506Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/5vepf09pddrm20che3r966e2d8", "cancel": "https://api.replicate.com/v1/predictions/5vepf09pddrm20che3r966e2d8/cancel" }, "version": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0" }Generated inUsing seed: 916 Prompt: GHIBSKY style, an orange Lamborghini driving down a hill road at night with a beautiful ocean view in the background, side view, no text txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.70it/s] 7%|▋ | 2/28 [00:00<00:06, 4.26it/s] 11%|█ | 3/28 [00:00<00:06, 4.00it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.89it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.82it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.76it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.75it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.74it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.73it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.73it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.73it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.72it/s] 50%|█████ | 14/28 [00:03<00:03, 3.72it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.72it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.72it/s] 61%|██████ | 17/28 [00:04<00:02, 3.71it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.72it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.72it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.72it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.72it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s] 100%|██████████| 28/28 [00:07<00:00, 3.72it/s] 100%|██████████| 28/28 [00:07<00:00, 3.74it/s]Prediction
aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0ID7favz0fss9rm20che3zv2x817mStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- GHIBSKY style, the most beautiful place in the universe
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 9:16
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 28
{ "model": "dev", "prompt": "GHIBSKY style, the most beautiful place in the universe", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", { input: { model: "dev", prompt: "GHIBSKY style, the most beautiful place in the universe", lora_scale: 1, num_outputs: 1, aspect_ratio: "9:16", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, 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 aleksa-codes/flux-ghibsky-illustration using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aleksa-codes/flux-ghibsky-illustration:a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", input={ "model": "dev", "prompt": "GHIBSKY style, the most beautiful place in the universe", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run aleksa-codes/flux-ghibsky-illustration 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": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", "input": { "model": "dev", "prompt": "GHIBSKY style, the most beautiful place in the universe", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "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": "2024-08-20T18:15:25.032852Z", "created_at": "2024-08-20T18:15:09.514000Z", "data_removed": false, "error": null, "id": "7favz0fss9rm20che3zv2x817m", "input": { "model": "dev", "prompt": "GHIBSKY style, the most beautiful place in the universe", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 }, "logs": "Using seed: 33150\nPrompt: GHIBSKY style, the most beautiful place in the universe\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.73it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.30it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.02it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.89it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.83it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.80it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.77it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.76it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.75it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.74it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.74it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.73it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.73it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.73it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.73it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.73it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.73it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.73it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.73it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.73it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.73it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.73it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.73it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.72it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.72it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.73it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.73it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.72it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.76it/s]", "metrics": { "predict_time": 15.493870966, "total_time": 15.518852 }, "output": [ "https://replicate.delivery/yhqm/BOHKpNOw2DrlFhbU6ohQpS7D3Lj2wA9PiMMedWkbPdKe8oUTA/out-0.jpg" ], "started_at": "2024-08-20T18:15:09.538981Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7favz0fss9rm20che3zv2x817m", "cancel": "https://api.replicate.com/v1/predictions/7favz0fss9rm20che3zv2x817m/cancel" }, "version": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0" }Generated inUsing seed: 33150 Prompt: GHIBSKY style, the most beautiful place in the universe txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.73it/s] 7%|▋ | 2/28 [00:00<00:06, 4.30it/s] 11%|█ | 3/28 [00:00<00:06, 4.02it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.89it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.83it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.80it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.77it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.76it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.75it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.74it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.74it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.73it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.73it/s] 50%|█████ | 14/28 [00:03<00:03, 3.73it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.73it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.73it/s] 61%|██████ | 17/28 [00:04<00:02, 3.73it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.73it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.73it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.73it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.73it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.73it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.73it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.72it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.72it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.73it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.73it/s] 100%|██████████| 28/28 [00:07<00:00, 3.72it/s] 100%|██████████| 28/28 [00:07<00:00, 3.76it/s]
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