cbh123 / sdxl-money
SDXL fine-tuned on currencies
- Public
- 5.6K runs
-
L40S
Prediction
cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515bID7h6rha3bjq3kfgu23f2dy4enyeStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1600
- height
- 800
- prompt
- an image in the style of TOK
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1600, "height": 800, "prompt": "an image in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cbh123/sdxl-money using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", { input: { width: 1600, height: 800, prompt: "an image in the style of TOK", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, prompt_strength: 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 replicate
Import the client:import replicate
Run cbh123/sdxl-money using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", input={ "width": 1600, "height": 800, "prompt": "an image in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run cbh123/sdxl-money 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": "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", "input": { "width": 1600, "height": 800, "prompt": "an image in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-08-22T20:23:13.771917Z", "created_at": "2023-08-22T20:22:53.653484Z", "data_removed": false, "error": null, "id": "7h6rha3bjq3kfgu23f2dy4enye", "input": { "width": 1600, "height": 800, "prompt": "an image in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 29386\nPrompt: an image in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:17, 2.84it/s]\n 4%|▍ | 2/50 [00:00<00:16, 2.84it/s]\n 6%|▌ | 3/50 [00:01<00:16, 2.84it/s]\n 8%|▊ | 4/50 [00:01<00:16, 2.84it/s]\n 10%|█ | 5/50 [00:01<00:15, 2.84it/s]\n 12%|█▏ | 6/50 [00:02<00:15, 2.84it/s]\n 14%|█▍ | 7/50 [00:02<00:15, 2.84it/s]\n 16%|█▌ | 8/50 [00:02<00:14, 2.83it/s]\n 18%|█▊ | 9/50 [00:03<00:14, 2.83it/s]\n 20%|██ | 10/50 [00:03<00:14, 2.83it/s]\n 22%|██▏ | 11/50 [00:03<00:13, 2.83it/s]\n 24%|██▍ | 12/50 [00:04<00:13, 2.83it/s]\n 26%|██▌ | 13/50 [00:04<00:13, 2.83it/s]\n 28%|██▊ | 14/50 [00:04<00:12, 2.83it/s]\n 30%|███ | 15/50 [00:05<00:12, 2.83it/s]\n 32%|███▏ | 16/50 [00:05<00:12, 2.83it/s]\n 34%|███▍ | 17/50 [00:06<00:11, 2.83it/s]\n 36%|███▌ | 18/50 [00:06<00:11, 2.83it/s]\n 38%|███▊ | 19/50 [00:06<00:10, 2.83it/s]\n 40%|████ | 20/50 [00:07<00:10, 2.83it/s]\n 42%|████▏ | 21/50 [00:07<00:10, 2.83it/s]\n 44%|████▍ | 22/50 [00:07<00:09, 2.82it/s]\n 46%|████▌ | 23/50 [00:08<00:09, 2.83it/s]\n 48%|████▊ | 24/50 [00:08<00:09, 2.83it/s]\n 50%|█████ | 25/50 [00:08<00:08, 2.82it/s]\n 52%|█████▏ | 26/50 [00:09<00:08, 2.82it/s]\n 54%|█████▍ | 27/50 [00:09<00:08, 2.82it/s]\n 56%|█████▌ | 28/50 [00:09<00:07, 2.82it/s]\n 58%|█████▊ | 29/50 [00:10<00:07, 2.82it/s]\n 60%|██████ | 30/50 [00:10<00:07, 2.82it/s]\n 62%|██████▏ | 31/50 [00:10<00:06, 2.82it/s]\n 64%|██████▍ | 32/50 [00:11<00:06, 2.82it/s]\n 66%|██████▌ | 33/50 [00:11<00:06, 2.82it/s]\n 68%|██████▊ | 34/50 [00:12<00:05, 2.82it/s]\n 70%|███████ | 35/50 [00:12<00:05, 2.82it/s]\n 72%|███████▏ | 36/50 [00:12<00:04, 2.82it/s]\n 74%|███████▍ | 37/50 [00:13<00:04, 2.82it/s]\n 76%|███████▌ | 38/50 [00:13<00:04, 2.82it/s]\n 78%|███████▊ | 39/50 [00:13<00:03, 2.82it/s]\n 80%|████████ | 40/50 [00:14<00:03, 2.82it/s]\n 82%|████████▏ | 41/50 [00:14<00:03, 2.82it/s]\n 84%|████████▍ | 42/50 [00:14<00:02, 2.82it/s]\n 86%|████████▌ | 43/50 [00:15<00:02, 2.82it/s]\n 88%|████████▊ | 44/50 [00:15<00:02, 2.82it/s]\n 90%|█████████ | 45/50 [00:15<00:01, 2.82it/s]\n 92%|█████████▏| 46/50 [00:16<00:01, 2.82it/s]\n 94%|█████████▍| 47/50 [00:16<00:01, 2.82it/s]\n 96%|█████████▌| 48/50 [00:16<00:00, 2.82it/s]\n 98%|█████████▊| 49/50 [00:17<00:00, 2.82it/s]\n100%|██████████| 50/50 [00:17<00:00, 2.82it/s]\n100%|██████████| 50/50 [00:17<00:00, 2.83it/s]", "metrics": { "predict_time": 20.124109, "total_time": 20.118433 }, "output": [ "https://replicate.delivery/pbxt/ehFhi0tJVfqtokq5zXOXcrROlrhqjvOdZ8wvs8P499YwsscRA/out-0.png" ], "started_at": "2023-08-22T20:22:53.647808Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7h6rha3bjq3kfgu23f2dy4enye", "cancel": "https://api.replicate.com/v1/predictions/7h6rha3bjq3kfgu23f2dy4enye/cancel" }, "version": "2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b" }
Generated inUsing seed: 29386 Prompt: an image in the style of <s0><s1> txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:17, 2.84it/s] 4%|▍ | 2/50 [00:00<00:16, 2.84it/s] 6%|▌ | 3/50 [00:01<00:16, 2.84it/s] 8%|▊ | 4/50 [00:01<00:16, 2.84it/s] 10%|█ | 5/50 [00:01<00:15, 2.84it/s] 12%|█▏ | 6/50 [00:02<00:15, 2.84it/s] 14%|█▍ | 7/50 [00:02<00:15, 2.84it/s] 16%|█▌ | 8/50 [00:02<00:14, 2.83it/s] 18%|█▊ | 9/50 [00:03<00:14, 2.83it/s] 20%|██ | 10/50 [00:03<00:14, 2.83it/s] 22%|██▏ | 11/50 [00:03<00:13, 2.83it/s] 24%|██▍ | 12/50 [00:04<00:13, 2.83it/s] 26%|██▌ | 13/50 [00:04<00:13, 2.83it/s] 28%|██▊ | 14/50 [00:04<00:12, 2.83it/s] 30%|███ | 15/50 [00:05<00:12, 2.83it/s] 32%|███▏ | 16/50 [00:05<00:12, 2.83it/s] 34%|███▍ | 17/50 [00:06<00:11, 2.83it/s] 36%|███▌ | 18/50 [00:06<00:11, 2.83it/s] 38%|███▊ | 19/50 [00:06<00:10, 2.83it/s] 40%|████ | 20/50 [00:07<00:10, 2.83it/s] 42%|████▏ | 21/50 [00:07<00:10, 2.83it/s] 44%|████▍ | 22/50 [00:07<00:09, 2.82it/s] 46%|████▌ | 23/50 [00:08<00:09, 2.83it/s] 48%|████▊ | 24/50 [00:08<00:09, 2.83it/s] 50%|█████ | 25/50 [00:08<00:08, 2.82it/s] 52%|█████▏ | 26/50 [00:09<00:08, 2.82it/s] 54%|█████▍ | 27/50 [00:09<00:08, 2.82it/s] 56%|█████▌ | 28/50 [00:09<00:07, 2.82it/s] 58%|█████▊ | 29/50 [00:10<00:07, 2.82it/s] 60%|██████ | 30/50 [00:10<00:07, 2.82it/s] 62%|██████▏ | 31/50 [00:10<00:06, 2.82it/s] 64%|██████▍ | 32/50 [00:11<00:06, 2.82it/s] 66%|██████▌ | 33/50 [00:11<00:06, 2.82it/s] 68%|██████▊ | 34/50 [00:12<00:05, 2.82it/s] 70%|███████ | 35/50 [00:12<00:05, 2.82it/s] 72%|███████▏ | 36/50 [00:12<00:04, 2.82it/s] 74%|███████▍ | 37/50 [00:13<00:04, 2.82it/s] 76%|███████▌ | 38/50 [00:13<00:04, 2.82it/s] 78%|███████▊ | 39/50 [00:13<00:03, 2.82it/s] 80%|████████ | 40/50 [00:14<00:03, 2.82it/s] 82%|████████▏ | 41/50 [00:14<00:03, 2.82it/s] 84%|████████▍ | 42/50 [00:14<00:02, 2.82it/s] 86%|████████▌ | 43/50 [00:15<00:02, 2.82it/s] 88%|████████▊ | 44/50 [00:15<00:02, 2.82it/s] 90%|█████████ | 45/50 [00:15<00:01, 2.82it/s] 92%|█████████▏| 46/50 [00:16<00:01, 2.82it/s] 94%|█████████▍| 47/50 [00:16<00:01, 2.82it/s] 96%|█████████▌| 48/50 [00:16<00:00, 2.82it/s] 98%|█████████▊| 49/50 [00:17<00:00, 2.82it/s] 100%|██████████| 50/50 [00:17<00:00, 2.82it/s] 100%|██████████| 50/50 [00:17<00:00, 2.83it/s]
Prediction
cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515bIDhckzwn3bawghwji6p35meqkquuStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1600
- height
- 800
- prompt
- a cyborg on a bank note in the style of TOK
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1600, "height": 800, "prompt": "a cyborg on a bank note in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cbh123/sdxl-money using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", { input: { width: 1600, height: 800, prompt: "a cyborg on a bank note in the style of TOK", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, prompt_strength: 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 replicate
Import the client:import replicate
Run cbh123/sdxl-money using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", input={ "width": 1600, "height": 800, "prompt": "a cyborg on a bank note in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run cbh123/sdxl-money 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": "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", "input": { "width": 1600, "height": 800, "prompt": "a cyborg on a bank note in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-08-23T14:11:29.776938Z", "created_at": "2023-08-23T14:11:10.145804Z", "data_removed": false, "error": null, "id": "hckzwn3bawghwji6p35meqkquu", "input": { "width": 1600, "height": 800, "prompt": "a cyborg on a bank note in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 4032\nPrompt: a cyborg on a bank note in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:17, 2.86it/s]\n 4%|▍ | 2/50 [00:00<00:16, 2.86it/s]\n 6%|▌ | 3/50 [00:01<00:16, 2.86it/s]\n 8%|▊ | 4/50 [00:01<00:16, 2.86it/s]\n 10%|█ | 5/50 [00:01<00:15, 2.86it/s]\n 12%|█▏ | 6/50 [00:02<00:15, 2.85it/s]\n 14%|█▍ | 7/50 [00:02<00:15, 2.85it/s]\n 16%|█▌ | 8/50 [00:02<00:14, 2.85it/s]\n 18%|█▊ | 9/50 [00:03<00:14, 2.85it/s]\n 20%|██ | 10/50 [00:03<00:14, 2.85it/s]\n 22%|██▏ | 11/50 [00:03<00:13, 2.85it/s]\n 24%|██▍ | 12/50 [00:04<00:13, 2.85it/s]\n 26%|██▌ | 13/50 [00:04<00:12, 2.85it/s]\n 28%|██▊ | 14/50 [00:04<00:12, 2.85it/s]\n 30%|███ | 15/50 [00:05<00:12, 2.85it/s]\n 32%|███▏ | 16/50 [00:05<00:11, 2.85it/s]\n 34%|███▍ | 17/50 [00:05<00:11, 2.85it/s]\n 36%|███▌ | 18/50 [00:06<00:11, 2.85it/s]\n 38%|███▊ | 19/50 [00:06<00:10, 2.85it/s]\n 40%|████ | 20/50 [00:07<00:10, 2.85it/s]\n 42%|████▏ | 21/50 [00:07<00:10, 2.85it/s]\n 44%|████▍ | 22/50 [00:07<00:09, 2.84it/s]\n 46%|████▌ | 23/50 [00:08<00:09, 2.84it/s]\n 48%|████▊ | 24/50 [00:08<00:09, 2.84it/s]\n 50%|█████ | 25/50 [00:08<00:08, 2.84it/s]\n 52%|█████▏ | 26/50 [00:09<00:08, 2.84it/s]\n 54%|█████▍ | 27/50 [00:09<00:08, 2.84it/s]\n 56%|█████▌ | 28/50 [00:09<00:07, 2.84it/s]\n 58%|█████▊ | 29/50 [00:10<00:07, 2.84it/s]\n 60%|██████ | 30/50 [00:10<00:07, 2.84it/s]\n 62%|██████▏ | 31/50 [00:10<00:06, 2.84it/s]\n 64%|██████▍ | 32/50 [00:11<00:06, 2.84it/s]\n 66%|██████▌ | 33/50 [00:11<00:05, 2.84it/s]\n 68%|██████▊ | 34/50 [00:11<00:05, 2.84it/s]\n 70%|███████ | 35/50 [00:12<00:05, 2.84it/s]\n 72%|███████▏ | 36/50 [00:12<00:04, 2.84it/s]\n 74%|███████▍ | 37/50 [00:13<00:04, 2.84it/s]\n 76%|███████▌ | 38/50 [00:13<00:04, 2.84it/s]\n 78%|███████▊ | 39/50 [00:13<00:03, 2.84it/s]\n 80%|████████ | 40/50 [00:14<00:03, 2.84it/s]\n 82%|████████▏ | 41/50 [00:14<00:03, 2.84it/s]\n 84%|████████▍ | 42/50 [00:14<00:02, 2.84it/s]\n 86%|████████▌ | 43/50 [00:15<00:02, 2.84it/s]\n 88%|████████▊ | 44/50 [00:15<00:02, 2.84it/s]\n 90%|█████████ | 45/50 [00:15<00:01, 2.84it/s]\n 92%|█████████▏| 46/50 [00:16<00:01, 2.84it/s]\n 94%|█████████▍| 47/50 [00:16<00:01, 2.84it/s]\n 96%|█████████▌| 48/50 [00:16<00:00, 2.84it/s]\n 98%|█████████▊| 49/50 [00:17<00:00, 2.84it/s]\n100%|██████████| 50/50 [00:17<00:00, 2.84it/s]\n100%|██████████| 50/50 [00:17<00:00, 2.84it/s]", "metrics": { "predict_time": 19.689199, "total_time": 19.631134 }, "output": [ "https://replicate.delivery/pbxt/Cnqfb8cfUfD9nJgovAEFfoQWXQf9HjMNG5T96nHXd3wHyinLC/out-0.png" ], "started_at": "2023-08-23T14:11:10.087739Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/hckzwn3bawghwji6p35meqkquu", "cancel": "https://api.replicate.com/v1/predictions/hckzwn3bawghwji6p35meqkquu/cancel" }, "version": "2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b" }
Generated inUsing seed: 4032 Prompt: a cyborg on a bank note in the style of <s0><s1> txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:17, 2.86it/s] 4%|▍ | 2/50 [00:00<00:16, 2.86it/s] 6%|▌ | 3/50 [00:01<00:16, 2.86it/s] 8%|▊ | 4/50 [00:01<00:16, 2.86it/s] 10%|█ | 5/50 [00:01<00:15, 2.86it/s] 12%|█▏ | 6/50 [00:02<00:15, 2.85it/s] 14%|█▍ | 7/50 [00:02<00:15, 2.85it/s] 16%|█▌ | 8/50 [00:02<00:14, 2.85it/s] 18%|█▊ | 9/50 [00:03<00:14, 2.85it/s] 20%|██ | 10/50 [00:03<00:14, 2.85it/s] 22%|██▏ | 11/50 [00:03<00:13, 2.85it/s] 24%|██▍ | 12/50 [00:04<00:13, 2.85it/s] 26%|██▌ | 13/50 [00:04<00:12, 2.85it/s] 28%|██▊ | 14/50 [00:04<00:12, 2.85it/s] 30%|███ | 15/50 [00:05<00:12, 2.85it/s] 32%|███▏ | 16/50 [00:05<00:11, 2.85it/s] 34%|███▍ | 17/50 [00:05<00:11, 2.85it/s] 36%|███▌ | 18/50 [00:06<00:11, 2.85it/s] 38%|███▊ | 19/50 [00:06<00:10, 2.85it/s] 40%|████ | 20/50 [00:07<00:10, 2.85it/s] 42%|████▏ | 21/50 [00:07<00:10, 2.85it/s] 44%|████▍ | 22/50 [00:07<00:09, 2.84it/s] 46%|████▌ | 23/50 [00:08<00:09, 2.84it/s] 48%|████▊ | 24/50 [00:08<00:09, 2.84it/s] 50%|█████ | 25/50 [00:08<00:08, 2.84it/s] 52%|█████▏ | 26/50 [00:09<00:08, 2.84it/s] 54%|█████▍ | 27/50 [00:09<00:08, 2.84it/s] 56%|█████▌ | 28/50 [00:09<00:07, 2.84it/s] 58%|█████▊ | 29/50 [00:10<00:07, 2.84it/s] 60%|██████ | 30/50 [00:10<00:07, 2.84it/s] 62%|██████▏ | 31/50 [00:10<00:06, 2.84it/s] 64%|██████▍ | 32/50 [00:11<00:06, 2.84it/s] 66%|██████▌ | 33/50 [00:11<00:05, 2.84it/s] 68%|██████▊ | 34/50 [00:11<00:05, 2.84it/s] 70%|███████ | 35/50 [00:12<00:05, 2.84it/s] 72%|███████▏ | 36/50 [00:12<00:04, 2.84it/s] 74%|███████▍ | 37/50 [00:13<00:04, 2.84it/s] 76%|███████▌ | 38/50 [00:13<00:04, 2.84it/s] 78%|███████▊ | 39/50 [00:13<00:03, 2.84it/s] 80%|████████ | 40/50 [00:14<00:03, 2.84it/s] 82%|████████▏ | 41/50 [00:14<00:03, 2.84it/s] 84%|████████▍ | 42/50 [00:14<00:02, 2.84it/s] 86%|████████▌ | 43/50 [00:15<00:02, 2.84it/s] 88%|████████▊ | 44/50 [00:15<00:02, 2.84it/s] 90%|█████████ | 45/50 [00:15<00:01, 2.84it/s] 92%|█████████▏| 46/50 [00:16<00:01, 2.84it/s] 94%|█████████▍| 47/50 [00:16<00:01, 2.84it/s] 96%|█████████▌| 48/50 [00:16<00:00, 2.84it/s] 98%|█████████▊| 49/50 [00:17<00:00, 2.84it/s] 100%|██████████| 50/50 [00:17<00:00, 2.84it/s] 100%|██████████| 50/50 [00:17<00:00, 2.84it/s]
Prediction
cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515bIDx77lu23biki7w2uspexqxbmdrmStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedby @cbh123Input
- width
- 1600
- height
- 800
- prompt
- a currency in the style of TOK
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 4
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- two heads
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1600, "height": 800, "prompt": "a currency in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "two heads", "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cbh123/sdxl-money using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", { input: { width: 1600, height: 800, prompt: "a currency in the style of TOK", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 4, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "two heads", prompt_strength: 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 replicate
Import the client:import replicate
Run cbh123/sdxl-money using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", input={ "width": 1600, "height": 800, "prompt": "a currency in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "two heads", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run cbh123/sdxl-money 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": "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", "input": { "width": 1600, "height": 800, "prompt": "a currency in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "two heads", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-08-22T20:22:16.599109Z", "created_at": "2023-08-22T20:21:07.807628Z", "data_removed": false, "error": null, "id": "x77lu23biki7w2uspexqxbmdrm", "input": { "width": 1600, "height": 800, "prompt": "a currency in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "two heads", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 48252\nPrompt: a currency in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:01<00:59, 1.22s/it]\n 4%|▍ | 2/50 [00:02<00:58, 1.22s/it]\n 6%|▌ | 3/50 [00:03<00:57, 1.22s/it]\n 8%|▊ | 4/50 [00:04<00:56, 1.22s/it]\n 10%|█ | 5/50 [00:06<00:54, 1.22s/it]\n 12%|█▏ | 6/50 [00:07<00:53, 1.22s/it]\n 14%|█▍ | 7/50 [00:08<00:52, 1.22s/it]\n 16%|█▌ | 8/50 [00:09<00:51, 1.22s/it]\n 18%|█▊ | 9/50 [00:11<00:50, 1.23s/it]\n 20%|██ | 10/50 [00:12<00:49, 1.23s/it]\n 22%|██▏ | 11/50 [00:13<00:47, 1.23s/it]\n 24%|██▍ | 12/50 [00:14<00:46, 1.23s/it]\n 26%|██▌ | 13/50 [00:15<00:45, 1.23s/it]\n 28%|██▊ | 14/50 [00:17<00:44, 1.23s/it]\n 30%|███ | 15/50 [00:18<00:43, 1.23s/it]\n 32%|███▏ | 16/50 [00:19<00:41, 1.23s/it]\n 34%|███▍ | 17/50 [00:20<00:40, 1.23s/it]\n 36%|███▌ | 18/50 [00:22<00:39, 1.23s/it]\n 38%|███▊ | 19/50 [00:23<00:38, 1.23s/it]\n 40%|████ | 20/50 [00:24<00:36, 1.23s/it]\n 42%|████▏ | 21/50 [00:25<00:35, 1.23s/it]\n 44%|████▍ | 22/50 [00:26<00:34, 1.23s/it]\n 46%|████▌ | 23/50 [00:28<00:33, 1.23s/it]\n 48%|████▊ | 24/50 [00:29<00:31, 1.23s/it]\n 50%|█████ | 25/50 [00:30<00:30, 1.23s/it]\n 52%|█████▏ | 26/50 [00:31<00:29, 1.23s/it]\n 54%|█████▍ | 27/50 [00:33<00:28, 1.23s/it]\n 56%|█████▌ | 28/50 [00:34<00:27, 1.23s/it]\n 58%|█████▊ | 29/50 [00:35<00:25, 1.23s/it]\n 60%|██████ | 30/50 [00:36<00:24, 1.23s/it]\n 62%|██████▏ | 31/50 [00:38<00:23, 1.23s/it]\n 64%|██████▍ | 32/50 [00:39<00:22, 1.23s/it]\n 66%|██████▌ | 33/50 [00:40<00:20, 1.23s/it]\n 68%|██████▊ | 34/50 [00:41<00:19, 1.23s/it]\n 70%|███████ | 35/50 [00:42<00:18, 1.23s/it]\n 72%|███████▏ | 36/50 [00:44<00:17, 1.23s/it]\n 74%|███████▍ | 37/50 [00:45<00:16, 1.23s/it]\n 76%|███████▌ | 38/50 [00:46<00:14, 1.23s/it]\n 78%|███████▊ | 39/50 [00:47<00:13, 1.23s/it]\n 80%|████████ | 40/50 [00:49<00:12, 1.23s/it]\n 82%|████████▏ | 41/50 [00:50<00:11, 1.23s/it]\n 84%|████████▍ | 42/50 [00:51<00:09, 1.23s/it]\n 86%|████████▌ | 43/50 [00:52<00:08, 1.23s/it]\n 88%|████████▊ | 44/50 [00:54<00:07, 1.23s/it]\n 90%|█████████ | 45/50 [00:55<00:06, 1.24s/it]\n 92%|█████████▏| 46/50 [00:56<00:04, 1.23s/it]\n 94%|█████████▍| 47/50 [00:57<00:03, 1.24s/it]\n 96%|█████████▌| 48/50 [00:59<00:02, 1.24s/it]\n 98%|█████████▊| 49/50 [01:00<00:01, 1.24s/it]\n100%|██████████| 50/50 [01:01<00:00, 1.24s/it]\n100%|██████████| 50/50 [01:01<00:00, 1.23s/it]", "metrics": { "predict_time": 68.869153, "total_time": 68.791481 }, "output": [ "https://replicate.delivery/pbxt/cnXPfzxVfJhgDEGTOPVfC3xqdedlaVx6gZdLJcrg3DNWvyyFB/out-0.png", "https://replicate.delivery/pbxt/ViMZlfVwF41pZ6BEBOgS5sjohsqZU7wFBnBrD5WLLPO7VWuIA/out-1.png", "https://replicate.delivery/pbxt/XVdUMCjhL4ovFZHQjexcIceNSDxF1Lgf2uuafYAM6PadvyyFB/out-2.png", "https://replicate.delivery/pbxt/nJ6gSDLokRb2A1mtpO0oqCdrO2MIqIRQO97UfSWgLVB8VWuIA/out-3.png" ], "started_at": "2023-08-22T20:21:07.729956Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/x77lu23biki7w2uspexqxbmdrm", "cancel": "https://api.replicate.com/v1/predictions/x77lu23biki7w2uspexqxbmdrm/cancel" }, "version": "2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b" }
Generated inUsing seed: 48252 Prompt: a currency in the style of <s0><s1> txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:01<00:59, 1.22s/it] 4%|▍ | 2/50 [00:02<00:58, 1.22s/it] 6%|▌ | 3/50 [00:03<00:57, 1.22s/it] 8%|▊ | 4/50 [00:04<00:56, 1.22s/it] 10%|█ | 5/50 [00:06<00:54, 1.22s/it] 12%|█▏ | 6/50 [00:07<00:53, 1.22s/it] 14%|█▍ | 7/50 [00:08<00:52, 1.22s/it] 16%|█▌ | 8/50 [00:09<00:51, 1.22s/it] 18%|█▊ | 9/50 [00:11<00:50, 1.23s/it] 20%|██ | 10/50 [00:12<00:49, 1.23s/it] 22%|██▏ | 11/50 [00:13<00:47, 1.23s/it] 24%|██▍ | 12/50 [00:14<00:46, 1.23s/it] 26%|██▌ | 13/50 [00:15<00:45, 1.23s/it] 28%|██▊ | 14/50 [00:17<00:44, 1.23s/it] 30%|███ | 15/50 [00:18<00:43, 1.23s/it] 32%|███▏ | 16/50 [00:19<00:41, 1.23s/it] 34%|███▍ | 17/50 [00:20<00:40, 1.23s/it] 36%|███▌ | 18/50 [00:22<00:39, 1.23s/it] 38%|███▊ | 19/50 [00:23<00:38, 1.23s/it] 40%|████ | 20/50 [00:24<00:36, 1.23s/it] 42%|████▏ | 21/50 [00:25<00:35, 1.23s/it] 44%|████▍ | 22/50 [00:26<00:34, 1.23s/it] 46%|████▌ | 23/50 [00:28<00:33, 1.23s/it] 48%|████▊ | 24/50 [00:29<00:31, 1.23s/it] 50%|█████ | 25/50 [00:30<00:30, 1.23s/it] 52%|█████▏ | 26/50 [00:31<00:29, 1.23s/it] 54%|█████▍ | 27/50 [00:33<00:28, 1.23s/it] 56%|█████▌ | 28/50 [00:34<00:27, 1.23s/it] 58%|█████▊ | 29/50 [00:35<00:25, 1.23s/it] 60%|██████ | 30/50 [00:36<00:24, 1.23s/it] 62%|██████▏ | 31/50 [00:38<00:23, 1.23s/it] 64%|██████▍ | 32/50 [00:39<00:22, 1.23s/it] 66%|██████▌ | 33/50 [00:40<00:20, 1.23s/it] 68%|██████▊ | 34/50 [00:41<00:19, 1.23s/it] 70%|███████ | 35/50 [00:42<00:18, 1.23s/it] 72%|███████▏ | 36/50 [00:44<00:17, 1.23s/it] 74%|███████▍ | 37/50 [00:45<00:16, 1.23s/it] 76%|███████▌ | 38/50 [00:46<00:14, 1.23s/it] 78%|███████▊ | 39/50 [00:47<00:13, 1.23s/it] 80%|████████ | 40/50 [00:49<00:12, 1.23s/it] 82%|████████▏ | 41/50 [00:50<00:11, 1.23s/it] 84%|████████▍ | 42/50 [00:51<00:09, 1.23s/it] 86%|████████▌ | 43/50 [00:52<00:08, 1.23s/it] 88%|████████▊ | 44/50 [00:54<00:07, 1.23s/it] 90%|█████████ | 45/50 [00:55<00:06, 1.24s/it] 92%|█████████▏| 46/50 [00:56<00:04, 1.23s/it] 94%|█████████▍| 47/50 [00:57<00:03, 1.24s/it] 96%|█████████▌| 48/50 [00:59<00:02, 1.24s/it] 98%|█████████▊| 49/50 [01:00<00:01, 1.24s/it] 100%|██████████| 50/50 [01:01<00:00, 1.24s/it] 100%|██████████| 50/50 [01:01<00:00, 1.23s/it]
Prediction
cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515bIDafvx4etbuddy5yljwkmdkn2t4eStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1600
- height
- 800
- prompt
- an image in the style of TOK
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 4
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1600, "height": 800, "prompt": "an image in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cbh123/sdxl-money using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", { input: { width: 1600, height: 800, prompt: "an image in the style of TOK", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 4, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, prompt_strength: 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 replicate
Import the client:import replicate
Run cbh123/sdxl-money using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", input={ "width": 1600, "height": 800, "prompt": "an image in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run cbh123/sdxl-money 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": "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", "input": { "width": 1600, "height": 800, "prompt": "an image in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-08-22T20:25:03.349978Z", "created_at": "2023-08-22T20:23:54.625151Z", "data_removed": false, "error": null, "id": "afvx4etbuddy5yljwkmdkn2t4e", "input": { "width": 1600, "height": 800, "prompt": "an image in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 59837\nPrompt: an image in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:01<00:59, 1.22s/it]\n 4%|▍ | 2/50 [00:02<00:58, 1.23s/it]\n 6%|▌ | 3/50 [00:03<00:57, 1.23s/it]\n 8%|▊ | 4/50 [00:04<00:56, 1.23s/it]\n 10%|█ | 5/50 [00:06<00:55, 1.23s/it]\n 12%|█▏ | 6/50 [00:07<00:53, 1.23s/it]\n 14%|█▍ | 7/50 [00:08<00:52, 1.23s/it]\n 16%|█▌ | 8/50 [00:09<00:51, 1.23s/it]\n 18%|█▊ | 9/50 [00:11<00:50, 1.23s/it]\n 20%|██ | 10/50 [00:12<00:49, 1.23s/it]\n 22%|██▏ | 11/50 [00:13<00:47, 1.23s/it]\n 24%|██▍ | 12/50 [00:14<00:46, 1.23s/it]\n 26%|██▌ | 13/50 [00:15<00:45, 1.23s/it]\n 28%|██▊ | 14/50 [00:17<00:44, 1.23s/it]\n 30%|███ | 15/50 [00:18<00:43, 1.23s/it]\n 32%|███▏ | 16/50 [00:19<00:41, 1.23s/it]\n 34%|███▍ | 17/50 [00:20<00:40, 1.23s/it]\n 36%|███▌ | 18/50 [00:22<00:39, 1.23s/it]\n 38%|███▊ | 19/50 [00:23<00:38, 1.23s/it]\n 40%|████ | 20/50 [00:24<00:36, 1.23s/it]\n 42%|████▏ | 21/50 [00:25<00:35, 1.23s/it]\n 44%|████▍ | 22/50 [00:27<00:34, 1.23s/it]\n 46%|████▌ | 23/50 [00:28<00:33, 1.23s/it]\n 48%|████▊ | 24/50 [00:29<00:32, 1.23s/it]\n 50%|█████ | 25/50 [00:30<00:30, 1.23s/it]\n 52%|█████▏ | 26/50 [00:31<00:29, 1.23s/it]\n 54%|█████▍ | 27/50 [00:33<00:28, 1.23s/it]\n 56%|█████▌ | 28/50 [00:34<00:27, 1.23s/it]\n 58%|█████▊ | 29/50 [00:35<00:25, 1.23s/it]\n 60%|██████ | 30/50 [00:36<00:24, 1.23s/it]\n 62%|██████▏ | 31/50 [00:38<00:23, 1.23s/it]\n 64%|██████▍ | 32/50 [00:39<00:22, 1.23s/it]\n 66%|██████▌ | 33/50 [00:40<00:20, 1.23s/it]\n 68%|██████▊ | 34/50 [00:41<00:19, 1.23s/it]\n 70%|███████ | 35/50 [00:43<00:18, 1.23s/it]\n 72%|███████▏ | 36/50 [00:44<00:17, 1.23s/it]\n 74%|███████▍ | 37/50 [00:45<00:16, 1.23s/it]\n 76%|███████▌ | 38/50 [00:46<00:14, 1.23s/it]\n 78%|███████▊ | 39/50 [00:47<00:13, 1.23s/it]\n 80%|████████ | 40/50 [00:49<00:12, 1.23s/it]\n 82%|████████▏ | 41/50 [00:50<00:11, 1.23s/it]\n 84%|████████▍ | 42/50 [00:51<00:09, 1.23s/it]\n 86%|████████▌ | 43/50 [00:52<00:08, 1.23s/it]\n 88%|████████▊ | 44/50 [00:54<00:07, 1.23s/it]\n 90%|█████████ | 45/50 [00:55<00:06, 1.23s/it]\n 92%|█████████▏| 46/50 [00:56<00:04, 1.24s/it]\n 94%|█████████▍| 47/50 [00:57<00:03, 1.24s/it]\n 96%|█████████▌| 48/50 [00:59<00:02, 1.24s/it]\n 98%|█████████▊| 49/50 [01:00<00:01, 1.24s/it]\n100%|██████████| 50/50 [01:01<00:00, 1.24s/it]\n100%|██████████| 50/50 [01:01<00:00, 1.23s/it]", "metrics": { "predict_time": 68.727508, "total_time": 68.724827 }, "output": [ "https://replicate.delivery/pbxt/wnjLIlhGbfS5LaSfXexjnsdCDVO9Vtmedpp1Z0amEPny5yyFB/out-0.png", "https://replicate.delivery/pbxt/WUPugPVwjyKCExJXCuazUlxmHvDZVkyTufjZ0mfvo6yduscRA/out-1.png", "https://replicate.delivery/pbxt/HhYpSp53KtqSJFufhCqYycsUmYbGdx7th8iPwUK5KbPPXWuIA/out-2.png", "https://replicate.delivery/pbxt/EbEvfSQlES3cRSjXjr6GGuOaXZ3MqVUrk8mvvZUupwlPXWuIA/out-3.png" ], "started_at": "2023-08-22T20:23:54.622470Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/afvx4etbuddy5yljwkmdkn2t4e", "cancel": "https://api.replicate.com/v1/predictions/afvx4etbuddy5yljwkmdkn2t4e/cancel" }, "version": "2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b" }
Generated inUsing seed: 59837 Prompt: an image in the style of <s0><s1> txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:01<00:59, 1.22s/it] 4%|▍ | 2/50 [00:02<00:58, 1.23s/it] 6%|▌ | 3/50 [00:03<00:57, 1.23s/it] 8%|▊ | 4/50 [00:04<00:56, 1.23s/it] 10%|█ | 5/50 [00:06<00:55, 1.23s/it] 12%|█▏ | 6/50 [00:07<00:53, 1.23s/it] 14%|█▍ | 7/50 [00:08<00:52, 1.23s/it] 16%|█▌ | 8/50 [00:09<00:51, 1.23s/it] 18%|█▊ | 9/50 [00:11<00:50, 1.23s/it] 20%|██ | 10/50 [00:12<00:49, 1.23s/it] 22%|██▏ | 11/50 [00:13<00:47, 1.23s/it] 24%|██▍ | 12/50 [00:14<00:46, 1.23s/it] 26%|██▌ | 13/50 [00:15<00:45, 1.23s/it] 28%|██▊ | 14/50 [00:17<00:44, 1.23s/it] 30%|███ | 15/50 [00:18<00:43, 1.23s/it] 32%|███▏ | 16/50 [00:19<00:41, 1.23s/it] 34%|███▍ | 17/50 [00:20<00:40, 1.23s/it] 36%|███▌ | 18/50 [00:22<00:39, 1.23s/it] 38%|███▊ | 19/50 [00:23<00:38, 1.23s/it] 40%|████ | 20/50 [00:24<00:36, 1.23s/it] 42%|████▏ | 21/50 [00:25<00:35, 1.23s/it] 44%|████▍ | 22/50 [00:27<00:34, 1.23s/it] 46%|████▌ | 23/50 [00:28<00:33, 1.23s/it] 48%|████▊ | 24/50 [00:29<00:32, 1.23s/it] 50%|█████ | 25/50 [00:30<00:30, 1.23s/it] 52%|█████▏ | 26/50 [00:31<00:29, 1.23s/it] 54%|█████▍ | 27/50 [00:33<00:28, 1.23s/it] 56%|█████▌ | 28/50 [00:34<00:27, 1.23s/it] 58%|█████▊ | 29/50 [00:35<00:25, 1.23s/it] 60%|██████ | 30/50 [00:36<00:24, 1.23s/it] 62%|██████▏ | 31/50 [00:38<00:23, 1.23s/it] 64%|██████▍ | 32/50 [00:39<00:22, 1.23s/it] 66%|██████▌ | 33/50 [00:40<00:20, 1.23s/it] 68%|██████▊ | 34/50 [00:41<00:19, 1.23s/it] 70%|███████ | 35/50 [00:43<00:18, 1.23s/it] 72%|███████▏ | 36/50 [00:44<00:17, 1.23s/it] 74%|███████▍ | 37/50 [00:45<00:16, 1.23s/it] 76%|███████▌ | 38/50 [00:46<00:14, 1.23s/it] 78%|███████▊ | 39/50 [00:47<00:13, 1.23s/it] 80%|████████ | 40/50 [00:49<00:12, 1.23s/it] 82%|████████▏ | 41/50 [00:50<00:11, 1.23s/it] 84%|████████▍ | 42/50 [00:51<00:09, 1.23s/it] 86%|████████▌ | 43/50 [00:52<00:08, 1.23s/it] 88%|████████▊ | 44/50 [00:54<00:07, 1.23s/it] 90%|█████████ | 45/50 [00:55<00:06, 1.23s/it] 92%|█████████▏| 46/50 [00:56<00:04, 1.24s/it] 94%|█████████▍| 47/50 [00:57<00:03, 1.24s/it] 96%|█████████▌| 48/50 [00:59<00:02, 1.24s/it] 98%|█████████▊| 49/50 [01:00<00:01, 1.24s/it] 100%|██████████| 50/50 [01:01<00:00, 1.24s/it] 100%|██████████| 50/50 [01:01<00:00, 1.23s/it]
Prediction
cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515bID3mspxndbzgbcr24dz25t2n4uomStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedby @cbh123Input
- width
- 1600
- height
- 800
- prompt
- barbie on a bank note in the style of TOK
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1600, "height": 800, "prompt": "barbie on a bank note in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cbh123/sdxl-money using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", { input: { width: 1600, height: 800, prompt: "barbie on a bank note in the style of TOK", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, prompt_strength: 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 replicate
Import the client:import replicate
Run cbh123/sdxl-money using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", input={ "width": 1600, "height": 800, "prompt": "barbie on a bank note in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run cbh123/sdxl-money 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": "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", "input": { "width": 1600, "height": 800, "prompt": "barbie on a bank note in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-08-23T14:14:58.971213Z", "created_at": "2023-08-23T14:14:39.279407Z", "data_removed": false, "error": null, "id": "3mspxndbzgbcr24dz25t2n4uom", "input": { "width": 1600, "height": 800, "prompt": "barbie on a bank note in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 43229\nPrompt: barbie on a bank note in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:17, 2.87it/s]\n 4%|▍ | 2/50 [00:00<00:16, 2.86it/s]\n 6%|▌ | 3/50 [00:01<00:16, 2.86it/s]\n 8%|▊ | 4/50 [00:01<00:16, 2.85it/s]\n 10%|█ | 5/50 [00:01<00:15, 2.85it/s]\n 12%|█▏ | 6/50 [00:02<00:15, 2.85it/s]\n 14%|█▍ | 7/50 [00:02<00:15, 2.85it/s]\n 16%|█▌ | 8/50 [00:02<00:14, 2.85it/s]\n 18%|█▊ | 9/50 [00:03<00:14, 2.85it/s]\n 20%|██ | 10/50 [00:03<00:14, 2.85it/s]\n 22%|██▏ | 11/50 [00:03<00:13, 2.85it/s]\n 24%|██▍ | 12/50 [00:04<00:13, 2.85it/s]\n 26%|██▌ | 13/50 [00:04<00:12, 2.85it/s]\n 28%|██▊ | 14/50 [00:04<00:12, 2.86it/s]\n 30%|███ | 15/50 [00:05<00:12, 2.86it/s]\n 32%|███▏ | 16/50 [00:05<00:11, 2.86it/s]\n 34%|███▍ | 17/50 [00:05<00:11, 2.86it/s]\n 36%|███▌ | 18/50 [00:06<00:11, 2.86it/s]\n 38%|███▊ | 19/50 [00:06<00:10, 2.86it/s]\n 40%|████ | 20/50 [00:07<00:10, 2.86it/s]\n 42%|████▏ | 21/50 [00:07<00:10, 2.86it/s]\n 44%|████▍ | 22/50 [00:07<00:09, 2.86it/s]\n 46%|████▌ | 23/50 [00:08<00:09, 2.86it/s]\n 48%|████▊ | 24/50 [00:08<00:09, 2.86it/s]\n 50%|█████ | 25/50 [00:08<00:08, 2.86it/s]\n 52%|█████▏ | 26/50 [00:09<00:08, 2.86it/s]\n 54%|█████▍ | 27/50 [00:09<00:08, 2.86it/s]\n 56%|█████▌ | 28/50 [00:09<00:07, 2.86it/s]\n 58%|█████▊ | 29/50 [00:10<00:07, 2.86it/s]\n 60%|██████ | 30/50 [00:10<00:07, 2.86it/s]\n 62%|██████▏ | 31/50 [00:10<00:06, 2.86it/s]\n 64%|██████▍ | 32/50 [00:11<00:06, 2.85it/s]\n 66%|██████▌ | 33/50 [00:11<00:05, 2.86it/s]\n 68%|██████▊ | 34/50 [00:11<00:05, 2.85it/s]\n 70%|███████ | 35/50 [00:12<00:05, 2.86it/s]\n 72%|███████▏ | 36/50 [00:12<00:04, 2.86it/s]\n 74%|███████▍ | 37/50 [00:12<00:04, 2.85it/s]\n 76%|███████▌ | 38/50 [00:13<00:04, 2.85it/s]\n 78%|███████▊ | 39/50 [00:13<00:03, 2.85it/s]\n 80%|████████ | 40/50 [00:14<00:03, 2.85it/s]\n 82%|████████▏ | 41/50 [00:14<00:03, 2.85it/s]\n 84%|████████▍ | 42/50 [00:14<00:02, 2.85it/s]\n 86%|████████▌ | 43/50 [00:15<00:02, 2.85it/s]\n 88%|████████▊ | 44/50 [00:15<00:02, 2.85it/s]\n 90%|█████████ | 45/50 [00:15<00:01, 2.85it/s]\n 92%|█████████▏| 46/50 [00:16<00:01, 2.85it/s]\n 94%|█████████▍| 47/50 [00:16<00:01, 2.85it/s]\n 96%|█████████▌| 48/50 [00:16<00:00, 2.85it/s]\n 98%|█████████▊| 49/50 [00:17<00:00, 2.85it/s]\n100%|██████████| 50/50 [00:17<00:00, 2.85it/s]\n100%|██████████| 50/50 [00:17<00:00, 2.85it/s]", "metrics": { "predict_time": 19.639068, "total_time": 19.691806 }, "output": [ "https://replicate.delivery/pbxt/gzxBZgmGiG40A5jfPpE9dYh9hm2DUaWi3YQMTaN0wnnwMecRA/out-0.png" ], "started_at": "2023-08-23T14:14:39.332145Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3mspxndbzgbcr24dz25t2n4uom", "cancel": "https://api.replicate.com/v1/predictions/3mspxndbzgbcr24dz25t2n4uom/cancel" }, "version": "2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b" }
Generated inUsing seed: 43229 Prompt: barbie on a bank note in the style of <s0><s1> txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:17, 2.87it/s] 4%|▍ | 2/50 [00:00<00:16, 2.86it/s] 6%|▌ | 3/50 [00:01<00:16, 2.86it/s] 8%|▊ | 4/50 [00:01<00:16, 2.85it/s] 10%|█ | 5/50 [00:01<00:15, 2.85it/s] 12%|█▏ | 6/50 [00:02<00:15, 2.85it/s] 14%|█▍ | 7/50 [00:02<00:15, 2.85it/s] 16%|█▌ | 8/50 [00:02<00:14, 2.85it/s] 18%|█▊ | 9/50 [00:03<00:14, 2.85it/s] 20%|██ | 10/50 [00:03<00:14, 2.85it/s] 22%|██▏ | 11/50 [00:03<00:13, 2.85it/s] 24%|██▍ | 12/50 [00:04<00:13, 2.85it/s] 26%|██▌ | 13/50 [00:04<00:12, 2.85it/s] 28%|██▊ | 14/50 [00:04<00:12, 2.86it/s] 30%|███ | 15/50 [00:05<00:12, 2.86it/s] 32%|███▏ | 16/50 [00:05<00:11, 2.86it/s] 34%|███▍ | 17/50 [00:05<00:11, 2.86it/s] 36%|███▌ | 18/50 [00:06<00:11, 2.86it/s] 38%|███▊ | 19/50 [00:06<00:10, 2.86it/s] 40%|████ | 20/50 [00:07<00:10, 2.86it/s] 42%|████▏ | 21/50 [00:07<00:10, 2.86it/s] 44%|████▍ | 22/50 [00:07<00:09, 2.86it/s] 46%|████▌ | 23/50 [00:08<00:09, 2.86it/s] 48%|████▊ | 24/50 [00:08<00:09, 2.86it/s] 50%|█████ | 25/50 [00:08<00:08, 2.86it/s] 52%|█████▏ | 26/50 [00:09<00:08, 2.86it/s] 54%|█████▍ | 27/50 [00:09<00:08, 2.86it/s] 56%|█████▌ | 28/50 [00:09<00:07, 2.86it/s] 58%|█████▊ | 29/50 [00:10<00:07, 2.86it/s] 60%|██████ | 30/50 [00:10<00:07, 2.86it/s] 62%|██████▏ | 31/50 [00:10<00:06, 2.86it/s] 64%|██████▍ | 32/50 [00:11<00:06, 2.85it/s] 66%|██████▌ | 33/50 [00:11<00:05, 2.86it/s] 68%|██████▊ | 34/50 [00:11<00:05, 2.85it/s] 70%|███████ | 35/50 [00:12<00:05, 2.86it/s] 72%|███████▏ | 36/50 [00:12<00:04, 2.86it/s] 74%|███████▍ | 37/50 [00:12<00:04, 2.85it/s] 76%|███████▌ | 38/50 [00:13<00:04, 2.85it/s] 78%|███████▊ | 39/50 [00:13<00:03, 2.85it/s] 80%|████████ | 40/50 [00:14<00:03, 2.85it/s] 82%|████████▏ | 41/50 [00:14<00:03, 2.85it/s] 84%|████████▍ | 42/50 [00:14<00:02, 2.85it/s] 86%|████████▌ | 43/50 [00:15<00:02, 2.85it/s] 88%|████████▊ | 44/50 [00:15<00:02, 2.85it/s] 90%|█████████ | 45/50 [00:15<00:01, 2.85it/s] 92%|█████████▏| 46/50 [00:16<00:01, 2.85it/s] 94%|█████████▍| 47/50 [00:16<00:01, 2.85it/s] 96%|█████████▌| 48/50 [00:16<00:00, 2.85it/s] 98%|█████████▊| 49/50 [00:17<00:00, 2.85it/s] 100%|██████████| 50/50 [00:17<00:00, 2.85it/s] 100%|██████████| 50/50 [00:17<00:00, 2.85it/s]
Prediction
cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515bID4ipwojtbzovo4g4qawqznj7sl4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1600
- height
- 800
- prompt
- a currency in the style of TOK
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1600, "height": 800, "prompt": "a currency in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cbh123/sdxl-money using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", { input: { width: 1600, height: 800, prompt: "a currency in the style of TOK", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, prompt_strength: 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 replicate
Import the client:import replicate
Run cbh123/sdxl-money using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", input={ "width": 1600, "height": 800, "prompt": "a currency in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run cbh123/sdxl-money 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": "cbh123/sdxl-money:2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b", "input": { "width": 1600, "height": 800, "prompt": "a currency in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-08-22T20:19:26.288349Z", "created_at": "2023-08-22T20:18:16.838583Z", "data_removed": false, "error": null, "id": "4ipwojtbzovo4g4qawqznj7sl4", "input": { "width": 1600, "height": 800, "prompt": "a currency in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 40871\nPrompt: a currency in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:44, 1.09it/s]\n 4%|▍ | 2/50 [00:01<00:27, 1.72it/s]\n 6%|▌ | 3/50 [00:01<00:22, 2.10it/s]\n 8%|▊ | 4/50 [00:01<00:19, 2.34it/s]\n 10%|█ | 5/50 [00:02<00:18, 2.50it/s]\n 12%|█▏ | 6/50 [00:02<00:16, 2.61it/s]\n 14%|█▍ | 7/50 [00:03<00:16, 2.68it/s]\n 16%|█▌ | 8/50 [00:03<00:15, 2.73it/s]\n 18%|█▊ | 9/50 [00:03<00:14, 2.76it/s]\n 20%|██ | 10/50 [00:04<00:14, 2.77it/s]\n 22%|██▏ | 11/50 [00:04<00:14, 2.78it/s]\n 24%|██▍ | 12/50 [00:04<00:13, 2.80it/s]\n 26%|██▌ | 13/50 [00:05<00:13, 2.81it/s]\n 28%|██▊ | 14/50 [00:05<00:12, 2.82it/s]\n 30%|███ | 15/50 [00:05<00:12, 2.82it/s]\n 32%|███▏ | 16/50 [00:06<00:12, 2.83it/s]\n 34%|███▍ | 17/50 [00:06<00:11, 2.83it/s]\n 36%|███▌ | 18/50 [00:06<00:11, 2.83it/s]\n 38%|███▊ | 19/50 [00:07<00:10, 2.83it/s]\n 40%|████ | 20/50 [00:07<00:10, 2.83it/s]\n 42%|████▏ | 21/50 [00:07<00:10, 2.83it/s]\n 44%|████▍ | 22/50 [00:08<00:09, 2.83it/s]\n 46%|████▌ | 23/50 [00:08<00:09, 2.83it/s]\n 48%|████▊ | 24/50 [00:09<00:09, 2.83it/s]\n 50%|█████ | 25/50 [00:09<00:08, 2.83it/s]\n 52%|█████▏ | 26/50 [00:09<00:08, 2.83it/s]\n 54%|█████▍ | 27/50 [00:10<00:08, 2.82it/s]\n 56%|█████▌ | 28/50 [00:10<00:07, 2.82it/s]\n 58%|█████▊ | 29/50 [00:10<00:07, 2.83it/s]\n 60%|██████ | 30/50 [00:11<00:07, 2.83it/s]\n 62%|██████▏ | 31/50 [00:11<00:06, 2.83it/s]\n 64%|██████▍ | 32/50 [00:11<00:06, 2.83it/s]\n 66%|██████▌ | 33/50 [00:12<00:06, 2.83it/s]\n 68%|██████▊ | 34/50 [00:12<00:05, 2.82it/s]\n 70%|███████ | 35/50 [00:12<00:05, 2.82it/s]\n 72%|███████▏ | 36/50 [00:13<00:04, 2.82it/s]\n 74%|███████▍ | 37/50 [00:13<00:04, 2.82it/s]\n 76%|███████▌ | 38/50 [00:13<00:04, 2.82it/s]\n 78%|███████▊ | 39/50 [00:14<00:03, 2.82it/s]\n 80%|████████ | 40/50 [00:14<00:03, 2.82it/s]\n 82%|████████▏ | 41/50 [00:15<00:03, 2.82it/s]\n 84%|████████▍ | 42/50 [00:15<00:02, 2.82it/s]\n 86%|████████▌ | 43/50 [00:15<00:02, 2.83it/s]\n 88%|████████▊ | 44/50 [00:16<00:02, 2.83it/s]\n 90%|█████████ | 45/50 [00:16<00:01, 2.83it/s]\n 92%|█████████▏| 46/50 [00:16<00:01, 2.83it/s]\n 94%|█████████▍| 47/50 [00:17<00:01, 2.83it/s]\n 96%|█████████▌| 48/50 [00:17<00:00, 2.83it/s]\n 98%|█████████▊| 49/50 [00:17<00:00, 2.83it/s]\n100%|██████████| 50/50 [00:18<00:00, 2.83it/s]\n100%|██████████| 50/50 [00:18<00:00, 2.74it/s]", "metrics": { "predict_time": 21.116445, "total_time": 69.449766 }, "output": [ "https://replicate.delivery/pbxt/nmQVQRvksCbZLha5QMK6XPyblARuAZhehJsoUngVtE8mUWuIA/out-0.png" ], "started_at": "2023-08-22T20:19:05.171904Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4ipwojtbzovo4g4qawqznj7sl4", "cancel": "https://api.replicate.com/v1/predictions/4ipwojtbzovo4g4qawqznj7sl4/cancel" }, "version": "2b730b5b15fbd334a1ade55b47c456577e2a732bab936c2882c60a09b2f5515b" }
Generated inUsing seed: 40871 Prompt: a currency in the style of <s0><s1> txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:44, 1.09it/s] 4%|▍ | 2/50 [00:01<00:27, 1.72it/s] 6%|▌ | 3/50 [00:01<00:22, 2.10it/s] 8%|▊ | 4/50 [00:01<00:19, 2.34it/s] 10%|█ | 5/50 [00:02<00:18, 2.50it/s] 12%|█▏ | 6/50 [00:02<00:16, 2.61it/s] 14%|█▍ | 7/50 [00:03<00:16, 2.68it/s] 16%|█▌ | 8/50 [00:03<00:15, 2.73it/s] 18%|█▊ | 9/50 [00:03<00:14, 2.76it/s] 20%|██ | 10/50 [00:04<00:14, 2.77it/s] 22%|██▏ | 11/50 [00:04<00:14, 2.78it/s] 24%|██▍ | 12/50 [00:04<00:13, 2.80it/s] 26%|██▌ | 13/50 [00:05<00:13, 2.81it/s] 28%|██▊ | 14/50 [00:05<00:12, 2.82it/s] 30%|███ | 15/50 [00:05<00:12, 2.82it/s] 32%|███▏ | 16/50 [00:06<00:12, 2.83it/s] 34%|███▍ | 17/50 [00:06<00:11, 2.83it/s] 36%|███▌ | 18/50 [00:06<00:11, 2.83it/s] 38%|███▊ | 19/50 [00:07<00:10, 2.83it/s] 40%|████ | 20/50 [00:07<00:10, 2.83it/s] 42%|████▏ | 21/50 [00:07<00:10, 2.83it/s] 44%|████▍ | 22/50 [00:08<00:09, 2.83it/s] 46%|████▌ | 23/50 [00:08<00:09, 2.83it/s] 48%|████▊ | 24/50 [00:09<00:09, 2.83it/s] 50%|█████ | 25/50 [00:09<00:08, 2.83it/s] 52%|█████▏ | 26/50 [00:09<00:08, 2.83it/s] 54%|█████▍ | 27/50 [00:10<00:08, 2.82it/s] 56%|█████▌ | 28/50 [00:10<00:07, 2.82it/s] 58%|█████▊ | 29/50 [00:10<00:07, 2.83it/s] 60%|██████ | 30/50 [00:11<00:07, 2.83it/s] 62%|██████▏ | 31/50 [00:11<00:06, 2.83it/s] 64%|██████▍ | 32/50 [00:11<00:06, 2.83it/s] 66%|██████▌ | 33/50 [00:12<00:06, 2.83it/s] 68%|██████▊ | 34/50 [00:12<00:05, 2.82it/s] 70%|███████ | 35/50 [00:12<00:05, 2.82it/s] 72%|███████▏ | 36/50 [00:13<00:04, 2.82it/s] 74%|███████▍ | 37/50 [00:13<00:04, 2.82it/s] 76%|███████▌ | 38/50 [00:13<00:04, 2.82it/s] 78%|███████▊ | 39/50 [00:14<00:03, 2.82it/s] 80%|████████ | 40/50 [00:14<00:03, 2.82it/s] 82%|████████▏ | 41/50 [00:15<00:03, 2.82it/s] 84%|████████▍ | 42/50 [00:15<00:02, 2.82it/s] 86%|████████▌ | 43/50 [00:15<00:02, 2.83it/s] 88%|████████▊ | 44/50 [00:16<00:02, 2.83it/s] 90%|█████████ | 45/50 [00:16<00:01, 2.83it/s] 92%|█████████▏| 46/50 [00:16<00:01, 2.83it/s] 94%|█████████▍| 47/50 [00:17<00:01, 2.83it/s] 96%|█████████▌| 48/50 [00:17<00:00, 2.83it/s] 98%|█████████▊| 49/50 [00:17<00:00, 2.83it/s] 100%|██████████| 50/50 [00:18<00:00, 2.83it/s] 100%|██████████| 50/50 [00:18<00:00, 2.74it/s]
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