wglint / 4_sdxl
Stable Diffusion XL - Refiner
- Public
- 126 runs
-
L40S
- GitHub
Prediction
wglint/4_sdxl:0d9ee66c19313abf6b553a95e10bd49be3e9dfe84393e548f29c304596eae6c1ID3uc77f3bhe4csy7dw7px7huucqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 1334
- width
- 1024
- height
- 1024
- prompt
- A studio photo of a rainbow coloured cat
- Refiner
- scheduler
- DDIM
- Refiner_noise
- 0.8
- guidance_scale
- 7.5
- number_picture
- 1
- negative_prompt
- num_inteference_steps
- 50
{ "seed": 1334, "width": 1024, "height": 1024, "prompt": "A studio photo of a rainbow coloured cat", "Refiner": true, "scheduler": "DDIM", "Refiner_noise": 0.8, "guidance_scale": 7.5, "number_picture": 1, "negative_prompt": "", "num_inteference_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 wglint/4_sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "wglint/4_sdxl:0d9ee66c19313abf6b553a95e10bd49be3e9dfe84393e548f29c304596eae6c1", { input: { seed: 1334, width: 1024, height: 1024, prompt: "A studio photo of a rainbow coloured cat", Refiner: true, scheduler: "DDIM", Refiner_noise: 0.8, guidance_scale: 7.5, number_picture: 1, negative_prompt: "", num_inteference_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 wglint/4_sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "wglint/4_sdxl:0d9ee66c19313abf6b553a95e10bd49be3e9dfe84393e548f29c304596eae6c1", input={ "seed": 1334, "width": 1024, "height": 1024, "prompt": "A studio photo of a rainbow coloured cat", "Refiner": True, "scheduler": "DDIM", "Refiner_noise": 0.8, "guidance_scale": 7.5, "number_picture": 1, "negative_prompt": "", "num_inteference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run wglint/4_sdxl 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": "wglint/4_sdxl:0d9ee66c19313abf6b553a95e10bd49be3e9dfe84393e548f29c304596eae6c1", "input": { "seed": 1334, "width": 1024, "height": 1024, "prompt": "A studio photo of a rainbow coloured cat", "Refiner": true, "scheduler": "DDIM", "Refiner_noise": 0.8, "guidance_scale": 7.5, "number_picture": 1, "negative_prompt": "", "num_inteference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-12-12T22:32:32.083023Z", "created_at": "2023-12-12T22:32:19.483459Z", "data_removed": false, "error": null, "id": "3uc77f3bhe4csy7dw7px7huucq", "input": { "seed": 1334, "width": 1024, "height": 1024, "prompt": "A studio photo of a rainbow coloured cat", "Refiner": true, "scheduler": "DDIM", "Refiner_noise": 0.8, "guidance_scale": 7.5, "number_picture": 1, "negative_prompt": "", "num_inteference_steps": 50 }, "logs": "Creating image with refiner model\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:07, 4.96it/s]\n 5%|▌ | 2/40 [00:00<00:07, 4.93it/s]\n 8%|▊ | 3/40 [00:00<00:07, 4.92it/s]\n 10%|█ | 4/40 [00:00<00:07, 4.91it/s]\n 12%|█▎ | 5/40 [00:01<00:07, 4.88it/s]\n 15%|█▌ | 6/40 [00:01<00:06, 4.88it/s]\n 18%|█▊ | 7/40 [00:01<00:06, 4.88it/s]\n 20%|██ | 8/40 [00:01<00:06, 4.88it/s]\n 22%|██▎ | 9/40 [00:01<00:06, 4.88it/s]\n 25%|██▌ | 10/40 [00:02<00:06, 4.87it/s]\n 28%|██▊ | 11/40 [00:02<00:05, 4.86it/s]\n 30%|███ | 12/40 [00:02<00:05, 4.87it/s]\n 32%|███▎ 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"2023-12-12T22:32:19.516173Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3uc77f3bhe4csy7dw7px7huucq", "cancel": "https://api.replicate.com/v1/predictions/3uc77f3bhe4csy7dw7px7huucq/cancel" }, "version": "0d9ee66c19313abf6b553a95e10bd49be3e9dfe84393e548f29c304596eae6c1" }Generated inCreating image with refiner model 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:07, 4.96it/s] 5%|▌ | 2/40 [00:00<00:07, 4.93it/s] 8%|▊ | 3/40 [00:00<00:07, 4.92it/s] 10%|█ | 4/40 [00:00<00:07, 4.91it/s] 12%|█▎ | 5/40 [00:01<00:07, 4.88it/s] 15%|█▌ | 6/40 [00:01<00:06, 4.88it/s] 18%|█▊ | 7/40 [00:01<00:06, 4.88it/s] 20%|██ | 8/40 [00:01<00:06, 4.88it/s] 22%|██▎ | 9/40 [00:01<00:06, 4.88it/s] 25%|██▌ | 10/40 [00:02<00:06, 4.87it/s] 28%|██▊ | 11/40 [00:02<00:05, 4.86it/s] 30%|███ | 12/40 [00:02<00:05, 4.87it/s] 32%|███▎ | 13/40 [00:02<00:05, 4.87it/s] 35%|███▌ | 14/40 [00:02<00:05, 4.87it/s] 38%|███▊ | 15/40 [00:03<00:05, 4.87it/s] 40%|████ | 16/40 [00:03<00:04, 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wglint/4_sdxl:0d9ee66c19313abf6b553a95e10bd49be3e9dfe84393e548f29c304596eae6c1ID3vkfe3dbeqaqt3puli4lj7waamStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 1334
- width
- 1024
- height
- 1024
- prompt
- A studio photo of a coloured cat
- Refiner
- scheduler
- DDIM
- Refiner_noise
- 0.8
- guidance_scale
- 7.5
- number_picture
- 1
- negative_prompt
- num_inteference_steps
- 50
{ "seed": 1334, "width": 1024, "height": 1024, "prompt": "A studio photo of a coloured cat", "Refiner": true, "scheduler": "DDIM", "Refiner_noise": 0.8, "guidance_scale": 7.5, "number_picture": 1, "negative_prompt": "", "num_inteference_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 wglint/4_sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "wglint/4_sdxl:0d9ee66c19313abf6b553a95e10bd49be3e9dfe84393e548f29c304596eae6c1", { input: { seed: 1334, width: 1024, height: 1024, prompt: "A studio photo of a coloured cat", Refiner: true, scheduler: "DDIM", Refiner_noise: 0.8, guidance_scale: 7.5, number_picture: 1, negative_prompt: "", num_inteference_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 wglint/4_sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "wglint/4_sdxl:0d9ee66c19313abf6b553a95e10bd49be3e9dfe84393e548f29c304596eae6c1", input={ "seed": 1334, "width": 1024, "height": 1024, "prompt": "A studio photo of a coloured cat", "Refiner": True, "scheduler": "DDIM", "Refiner_noise": 0.8, "guidance_scale": 7.5, "number_picture": 1, "negative_prompt": "", "num_inteference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run wglint/4_sdxl 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": "wglint/4_sdxl:0d9ee66c19313abf6b553a95e10bd49be3e9dfe84393e548f29c304596eae6c1", "input": { "seed": 1334, "width": 1024, "height": 1024, "prompt": "A studio photo of a coloured cat", "Refiner": true, "scheduler": "DDIM", "Refiner_noise": 0.8, "guidance_scale": 7.5, "number_picture": 1, "negative_prompt": "", "num_inteference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-12-12T22:32:57.813186Z", "created_at": "2023-12-12T22:32:45.142322Z", "data_removed": false, "error": null, "id": "3vkfe3dbeqaqt3puli4lj7waam", "input": { "seed": 1334, "width": 1024, "height": 1024, "prompt": "A studio photo of a coloured cat", "Refiner": true, "scheduler": "DDIM", "Refiner_noise": 0.8, "guidance_scale": 7.5, "number_picture": 1, "negative_prompt": "", "num_inteference_steps": 50 }, "logs": "Creating image with refiner model\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:07, 4.93it/s]\n 5%|▌ | 2/40 [00:00<00:07, 4.92it/s]\n 8%|▊ | 3/40 [00:00<00:07, 4.92it/s]\n 10%|█ | 4/40 [00:00<00:07, 4.92it/s]\n 12%|█▎ | 5/40 [00:01<00:07, 4.89it/s]\n 15%|█▌ | 6/40 [00:01<00:06, 4.88it/s]\n 18%|█▊ | 7/40 [00:01<00:06, 4.89it/s]\n 20%|██ | 8/40 [00:01<00:06, 4.89it/s]\n 22%|██▎ | 9/40 [00:01<00:06, 4.89it/s]\n 25%|██▌ | 10/40 [00:02<00:06, 4.88it/s]\n 28%|██▊ | 11/40 [00:02<00:05, 4.88it/s]\n 30%|███ | 12/40 [00:02<00:05, 4.88it/s]\n 32%|███▎ | 13/40 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[00:07<00:01, 4.88it/s]\n 90%|█████████ | 36/40 [00:07<00:00, 4.88it/s]\n 92%|█████████▎| 37/40 [00:07<00:00, 4.88it/s]\n 95%|█████████▌| 38/40 [00:07<00:00, 4.88it/s]\n 98%|█████████▊| 39/40 [00:07<00:00, 4.88it/s]\n100%|██████████| 40/40 [00:08<00:00, 4.88it/s]\n100%|██████████| 40/40 [00:08<00:00, 4.88it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 20%|██ | 2/10 [00:00<00:01, 6.32it/s]\n 30%|███ | 3/10 [00:00<00:01, 5.29it/s]\n 40%|████ | 4/10 [00:00<00:01, 4.87it/s]\n 50%|█████ | 5/10 [00:01<00:01, 4.65it/s]\n 60%|██████ | 6/10 [00:01<00:00, 4.52it/s]\n 70%|███████ | 7/10 [00:01<00:00, 4.44it/s]\n 80%|████████ | 8/10 [00:01<00:00, 4.40it/s]\n 90%|█████████ | 9/10 [00:01<00:00, 4.36it/s]\n100%|██████████| 10/10 [00:02<00:00, 4.34it/s]\n100%|██████████| 10/10 [00:02<00:00, 4.58it/s]", "metrics": { "predict_time": 12.637227, "total_time": 12.670864 }, "output": [ "https://replicate.delivery/pbxt/ATd13wXjzW5hEB9R2KfyBwZfGeI1cWhdVapI6SjOP9axMSDkA/generated-0.png" ], "started_at": "2023-12-12T22:32:45.175959Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3vkfe3dbeqaqt3puli4lj7waam", "cancel": "https://api.replicate.com/v1/predictions/3vkfe3dbeqaqt3puli4lj7waam/cancel" }, "version": "0d9ee66c19313abf6b553a95e10bd49be3e9dfe84393e548f29c304596eae6c1" }Generated inCreating image with refiner model 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:07, 4.93it/s] 5%|▌ | 2/40 [00:00<00:07, 4.92it/s] 8%|▊ | 3/40 [00:00<00:07, 4.92it/s] 10%|█ | 4/40 [00:00<00:07, 4.92it/s] 12%|█▎ | 5/40 [00:01<00:07, 4.89it/s] 15%|█▌ | 6/40 [00:01<00:06, 4.88it/s] 18%|█▊ | 7/40 [00:01<00:06, 4.89it/s] 20%|██ | 8/40 [00:01<00:06, 4.89it/s] 22%|██▎ | 9/40 [00:01<00:06, 4.89it/s] 25%|██▌ | 10/40 [00:02<00:06, 4.88it/s] 28%|██▊ | 11/40 [00:02<00:05, 4.88it/s] 30%|███ | 12/40 [00:02<00:05, 4.88it/s] 32%|███▎ | 13/40 [00:02<00:05, 4.88it/s] 35%|███▌ | 14/40 [00:02<00:05, 4.88it/s] 38%|███▊ | 15/40 [00:03<00:05, 4.88it/s] 40%|████ | 16/40 [00:03<00:04, 4.88it/s] 42%|████▎ | 17/40 [00:03<00:04, 4.88it/s] 45%|████▌ | 18/40 [00:03<00:04, 4.88it/s] 48%|████▊ | 19/40 [00:03<00:04, 4.89it/s] 50%|█████ | 20/40 [00:04<00:04, 4.89it/s] 52%|█████▎ | 21/40 [00:04<00:03, 4.89it/s] 55%|█████▌ | 22/40 [00:04<00:03, 4.89it/s] 57%|█████▊ | 23/40 [00:04<00:03, 4.89it/s] 60%|██████ | 24/40 [00:04<00:03, 4.89it/s] 62%|██████▎ | 25/40 [00:05<00:03, 4.88it/s] 65%|██████▌ | 26/40 [00:05<00:02, 4.88it/s] 68%|██████▊ | 27/40 [00:05<00:02, 4.89it/s] 70%|███████ | 28/40 [00:05<00:02, 4.88it/s] 72%|███████▎ | 29/40 [00:05<00:02, 4.88it/s] 75%|███████▌ | 30/40 [00:06<00:02, 4.88it/s] 78%|███████▊ | 31/40 [00:06<00:01, 4.88it/s] 80%|████████ | 32/40 [00:06<00:01, 4.88it/s] 82%|████████▎ | 33/40 [00:06<00:01, 4.89it/s] 85%|████████▌ | 34/40 [00:06<00:01, 4.88it/s] 88%|████████▊ | 35/40 [00:07<00:01, 4.88it/s] 90%|█████████ | 36/40 [00:07<00:00, 4.88it/s] 92%|█████████▎| 37/40 [00:07<00:00, 4.88it/s] 95%|█████████▌| 38/40 [00:07<00:00, 4.88it/s] 98%|█████████▊| 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