fofr
/
sdxl-jwst
- Public
- 418 runs
-
L40S
Prediction
fofr/sdxl-jwst:3c39ca4cID7wychklbgqpl3jo7ezlyewfmc4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a photo taken by TOK, astrophotography
- 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": 1024, "height": 1024, "prompt": "a photo taken by TOK, astrophotography", "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
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/sdxl-jwst using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-jwst:3c39ca4c9c8c1b3f1a5839fe46319da49baafeabed07c0741f43ac70e874de54", { input: { width: 1024, height: 1024, prompt: "a photo taken by TOK, astrophotography", 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 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client:import replicate
Run fofr/sdxl-jwst using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-jwst:3c39ca4c9c8c1b3f1a5839fe46319da49baafeabed07c0741f43ac70e874de54", input={ "width": 1024, "height": 1024, "prompt": "a photo taken by TOK, astrophotography", "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.
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/sdxl-jwst 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": "3c39ca4c9c8c1b3f1a5839fe46319da49baafeabed07c0741f43ac70e874de54", "input": { "width": 1024, "height": 1024, "prompt": "a photo taken by TOK, astrophotography", "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": "2023-08-14T21:13:17.861796Z", "created_at": "2023-08-14T21:12:22.099343Z", "data_removed": false, "error": null, "id": "7wychklbgqpl3jo7ezlyewfmc4", "input": { "width": 1024, "height": 1024, "prompt": "a photo taken by TOK, astrophotography", "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: 29382\nPrompt: a photo taken by <s0><s1>, astrophotography\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:01<00:49, 1.00s/it]\n 4%|▍ | 2/50 [00:02<00:48, 1.00s/it]\n 6%|▌ | 3/50 [00:03<00:47, 1.00s/it]\n 8%|▊ | 4/50 [00:04<00:46, 1.00s/it]\n 10%|█ | 5/50 [00:05<00:45, 1.01s/it]\n 12%|█▏ | 6/50 [00:06<00:44, 1.00s/it]\n 14%|█▍ | 7/50 [00:07<00:43, 1.00s/it]\n 16%|█▌ | 8/50 [00:08<00:42, 1.00s/it]\n 18%|█▊ | 9/50 [00:09<00:41, 1.00s/it]\n 20%|██ | 10/50 [00:10<00:40, 1.00s/it]\n 22%|██▏ | 11/50 [00:11<00:39, 1.00s/it]\n 24%|██▍ | 12/50 [00:12<00:38, 1.00s/it]\n 26%|██▌ | 13/50 [00:13<00:37, 1.00s/it]\n 28%|██▊ | 14/50 [00:14<00:36, 1.00s/it]\n 30%|███ | 15/50 [00:15<00:35, 1.00s/it]\n 32%|███▏ | 16/50 [00:16<00:34, 1.00s/it]\n 34%|███▍ | 17/50 [00:17<00:33, 1.00s/it]\n 36%|███▌ | 18/50 [00:18<00:32, 1.01s/it]\n 38%|███▊ | 19/50 [00:19<00:31, 1.01s/it]\n 40%|████ | 20/50 [00:20<00:30, 1.01s/it]\n 42%|████▏ | 21/50 [00:21<00:29, 1.01s/it]\n 44%|████▍ | 22/50 [00:22<00:28, 1.01s/it]\n 46%|████▌ | 23/50 [00:23<00:27, 1.01s/it]\n 48%|████▊ | 24/50 [00:24<00:26, 1.01s/it]\n 50%|█████ | 25/50 [00:25<00:25, 1.01s/it]\n 52%|█████▏ | 26/50 [00:26<00:24, 1.01s/it]\n 54%|█████▍ | 27/50 [00:27<00:23, 1.01s/it]\n 56%|█████▌ | 28/50 [00:28<00:22, 1.01s/it]\n 58%|█████▊ | 29/50 [00:29<00:21, 1.01s/it]\n 60%|██████ | 30/50 [00:30<00:20, 1.01s/it]\n 62%|██████▏ | 31/50 [00:31<00:19, 1.01s/it]\n 64%|██████▍ | 32/50 [00:32<00:18, 1.01s/it]\n 66%|██████▌ | 33/50 [00:33<00:17, 1.01s/it]\n 68%|██████▊ | 34/50 [00:34<00:16, 1.01s/it]\n 70%|███████ | 35/50 [00:35<00:15, 1.01s/it]\n 72%|███████▏ | 36/50 [00:36<00:14, 1.01s/it]\n 74%|███████▍ | 37/50 [00:37<00:13, 1.01s/it]\n 76%|███████▌ | 38/50 [00:38<00:12, 1.01s/it]\n 78%|███████▊ | 39/50 [00:39<00:11, 1.01s/it]\n 80%|████████ | 40/50 [00:40<00:10, 1.01s/it]\n 82%|████████▏ | 41/50 [00:41<00:09, 1.01s/it]\n 84%|████████▍ | 42/50 [00:42<00:08, 1.01s/it]\n 86%|████████▌ | 43/50 [00:43<00:07, 1.01s/it]\n 88%|████████▊ | 44/50 [00:44<00:06, 1.01s/it]\n 90%|█████████ | 45/50 [00:45<00:05, 1.01s/it]\n 92%|█████████▏| 46/50 [00:46<00:04, 1.01s/it]\n 94%|█████████▍| 47/50 [00:47<00:03, 1.01s/it]\n 96%|█████████▌| 48/50 [00:48<00:02, 1.01s/it]\n 98%|█████████▊| 49/50 [00:49<00:01, 1.01s/it]\n100%|██████████| 50/50 [00:50<00:00, 1.01s/it]\n100%|██████████| 50/50 [00:50<00:00, 1.01s/it]", "metrics": { "predict_time": 55.914082, "total_time": 55.762453 }, "output": [ "https://replicate.delivery/pbxt/5pmdyTXtQvryPhtK2V8jvPQiylKEBq0yzADahshObkG7KhWE/out-0.png", "https://replicate.delivery/pbxt/GGBcaHYf1qzjEKHVNEHM1UvxNnAhOqDEBxESJyjz2fMsrEaRA/out-1.png", "https://replicate.delivery/pbxt/zjiEnVPZMKZWHxvDMBRAxkhpj5PvwbglG69eTNcOzwj2VCtIA/out-2.png", "https://replicate.delivery/pbxt/y4EkIGL4G1byOlHY1FfBJkd5BsdRHms4qMk77Uog4Pt2VCtIA/out-3.png" ], "started_at": "2023-08-14T21:12:21.947714Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7wychklbgqpl3jo7ezlyewfmc4", "cancel": "https://api.replicate.com/v1/predictions/7wychklbgqpl3jo7ezlyewfmc4/cancel" }, "version": "3c39ca4c9c8c1b3f1a5839fe46319da49baafeabed07c0741f43ac70e874de54" }
Generated inUsing seed: 29382 Prompt: a photo taken by <s0><s1>, astrophotography txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:01<00:49, 1.00s/it] 4%|▍ | 2/50 [00:02<00:48, 1.00s/it] 6%|▌ | 3/50 [00:03<00:47, 1.00s/it] 8%|▊ | 4/50 [00:04<00:46, 1.00s/it] 10%|█ | 5/50 [00:05<00:45, 1.01s/it] 12%|█▏ | 6/50 [00:06<00:44, 1.00s/it] 14%|█▍ | 7/50 [00:07<00:43, 1.00s/it] 16%|█▌ | 8/50 [00:08<00:42, 1.00s/it] 18%|█▊ | 9/50 [00:09<00:41, 1.00s/it] 20%|██ | 10/50 [00:10<00:40, 1.00s/it] 22%|██▏ | 11/50 [00:11<00:39, 1.00s/it] 24%|██▍ | 12/50 [00:12<00:38, 1.00s/it] 26%|██▌ | 13/50 [00:13<00:37, 1.00s/it] 28%|██▊ | 14/50 [00:14<00:36, 1.00s/it] 30%|███ | 15/50 [00:15<00:35, 1.00s/it] 32%|███▏ | 16/50 [00:16<00:34, 1.00s/it] 34%|███▍ | 17/50 [00:17<00:33, 1.00s/it] 36%|███▌ | 18/50 [00:18<00:32, 1.01s/it] 38%|███▊ | 19/50 [00:19<00:31, 1.01s/it] 40%|████ | 20/50 [00:20<00:30, 1.01s/it] 42%|████▏ | 21/50 [00:21<00:29, 1.01s/it] 44%|████▍ | 22/50 [00:22<00:28, 1.01s/it] 46%|████▌ | 23/50 [00:23<00:27, 1.01s/it] 48%|████▊ | 24/50 [00:24<00:26, 1.01s/it] 50%|█████ | 25/50 [00:25<00:25, 1.01s/it] 52%|█████▏ | 26/50 [00:26<00:24, 1.01s/it] 54%|█████▍ | 27/50 [00:27<00:23, 1.01s/it] 56%|█████▌ | 28/50 [00:28<00:22, 1.01s/it] 58%|█████▊ | 29/50 [00:29<00:21, 1.01s/it] 60%|██████ | 30/50 [00:30<00:20, 1.01s/it] 62%|██████▏ | 31/50 [00:31<00:19, 1.01s/it] 64%|██████▍ | 32/50 [00:32<00:18, 1.01s/it] 66%|██████▌ | 33/50 [00:33<00:17, 1.01s/it] 68%|██████▊ | 34/50 [00:34<00:16, 1.01s/it] 70%|███████ | 35/50 [00:35<00:15, 1.01s/it] 72%|███████▏ | 36/50 [00:36<00:14, 1.01s/it] 74%|███████▍ | 37/50 [00:37<00:13, 1.01s/it] 76%|███████▌ | 38/50 [00:38<00:12, 1.01s/it] 78%|███████▊ | 39/50 [00:39<00:11, 1.01s/it] 80%|████████ | 40/50 [00:40<00:10, 1.01s/it] 82%|████████▏ | 41/50 [00:41<00:09, 1.01s/it] 84%|████████▍ | 42/50 [00:42<00:08, 1.01s/it] 86%|████████▌ | 43/50 [00:43<00:07, 1.01s/it] 88%|████████▊ | 44/50 [00:44<00:06, 1.01s/it] 90%|█████████ | 45/50 [00:45<00:05, 1.01s/it] 92%|█████████▏| 46/50 [00:46<00:04, 1.01s/it] 94%|█████████▍| 47/50 [00:47<00:03, 1.01s/it] 96%|█████████▌| 48/50 [00:48<00:02, 1.01s/it] 98%|█████████▊| 49/50 [00:49<00:01, 1.01s/it] 100%|██████████| 50/50 [00:50<00:00, 1.01s/it] 100%|██████████| 50/50 [00:50<00:00, 1.01s/it]
Prediction
fofr/sdxl-jwst:3c39ca4cID6rwhs6tbuli4mwqrdt7gxq3douStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 768
- height
- 1152
- prompt
- a night time landscape photo taken by TOK, blue pleiades, mountain, snow, astrophotography, beautiful, big sky
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.73
- num_outputs
- 4
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- milky way, daytime
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 768, "height": 1152, "prompt": "a night time landscape photo taken by TOK, blue pleiades, mountain, snow, astrophotography, beautiful, big sky", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.73, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "milky way, daytime", "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/sdxl-jwst using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-jwst:3c39ca4c9c8c1b3f1a5839fe46319da49baafeabed07c0741f43ac70e874de54", { input: { width: 768, height: 1152, prompt: "a night time landscape photo taken by TOK, blue pleiades, mountain, snow, astrophotography, beautiful, big sky", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.73, num_outputs: 4, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.8, negative_prompt: "milky way, daytime", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client:import replicate
Run fofr/sdxl-jwst using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-jwst:3c39ca4c9c8c1b3f1a5839fe46319da49baafeabed07c0741f43ac70e874de54", input={ "width": 768, "height": 1152, "prompt": "a night time landscape photo taken by TOK, blue pleiades, mountain, snow, astrophotography, beautiful, big sky", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.73, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.8, "negative_prompt": "milky way, daytime", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/sdxl-jwst 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": "3c39ca4c9c8c1b3f1a5839fe46319da49baafeabed07c0741f43ac70e874de54", "input": { "width": 768, "height": 1152, "prompt": "a night time landscape photo taken by TOK, blue pleiades, mountain, snow, astrophotography, beautiful, big sky", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.73, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "milky way, daytime", "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": "2023-08-15T20:37:47.766194Z", "created_at": "2023-08-15T20:35:37.071047Z", "data_removed": false, "error": null, "id": "6rwhs6tbuli4mwqrdt7gxq3dou", "input": { "width": 768, "height": 1152, "prompt": "a night time landscape photo taken by TOK, blue pleiades, mountain, snow, astrophotography, beautiful, big sky", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.73, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "milky way, daytime", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 34562\nPrompt: a night time landscape photo taken by <s0><s1>, blue pleiades, mountain, snow, astrophotography, beautiful, big sky\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:01<01:06, 1.35s/it]\n 4%|▍ | 2/50 [00:02<00:50, 1.06s/it]\n 6%|▌ | 3/50 [00:03<00:45, 1.04it/s]\n 8%|▊ | 4/50 [00:03<00:42, 1.08it/s]\n 10%|█ | 5/50 [00:04<00:40, 1.11it/s]\n 12%|█▏ | 6/50 [00:05<00:38, 1.13it/s]\n 14%|█▍ | 7/50 [00:06<00:37, 1.15it/s]\n 16%|█▌ | 8/50 [00:07<00:36, 1.16it/s]\n 18%|█▊ | 9/50 [00:08<00:35, 1.16it/s]\n 20%|██ | 10/50 [00:09<00:34, 1.17it/s]\n 22%|██▏ | 11/50 [00:09<00:33, 1.17it/s]\n 24%|██▍ | 12/50 [00:10<00:32, 1.17it/s]\n 26%|██▌ | 13/50 [00:11<00:31, 1.17it/s]\n 28%|██▊ | 14/50 [00:12<00:30, 1.17it/s]\n 30%|███ | 15/50 [00:13<00:29, 1.17it/s]\n 32%|███▏ | 16/50 [00:14<00:29, 1.17it/s]\n 34%|███▍ | 17/50 [00:14<00:28, 1.17it/s]\n 36%|███▌ | 18/50 [00:15<00:27, 1.17it/s]\n 38%|███▊ | 19/50 [00:16<00:26, 1.17it/s]\n 40%|████ | 20/50 [00:17<00:25, 1.17it/s]\n 42%|████▏ | 21/50 [00:18<00:24, 1.17it/s]\n 44%|████▍ | 22/50 [00:19<00:23, 1.17it/s]\n 46%|████▌ | 23/50 [00:20<00:23, 1.17it/s]\n 48%|████▊ | 24/50 [00:20<00:22, 1.17it/s]\n 50%|█████ | 25/50 [00:21<00:21, 1.17it/s]\n 52%|█████▏ | 26/50 [00:22<00:20, 1.17it/s]\n 54%|█████▍ | 27/50 [00:23<00:19, 1.17it/s]\n 56%|█████▌ | 28/50 [00:24<00:18, 1.17it/s]\n 58%|█████▊ | 29/50 [00:25<00:17, 1.17it/s]\n 60%|██████ | 30/50 [00:26<00:17, 1.17it/s]\n 62%|██████▏ | 31/50 [00:26<00:16, 1.17it/s]\n 64%|██████▍ | 32/50 [00:27<00:15, 1.17it/s]\n 66%|██████▌ | 33/50 [00:28<00:14, 1.17it/s]\n 68%|██████▊ | 34/50 [00:29<00:13, 1.17it/s]\n 70%|███████ | 35/50 [00:30<00:12, 1.17it/s]\n 72%|███████▏ | 36/50 [00:31<00:12, 1.17it/s]\n 74%|███████▍ | 37/50 [00:32<00:11, 1.17it/s]\n 76%|███████▌ | 38/50 [00:32<00:10, 1.17it/s]\n 78%|███████▊ | 39/50 [00:33<00:09, 1.17it/s]\n 80%|████████ | 40/50 [00:34<00:08, 1.16it/s]\n 82%|████████▏ | 41/50 [00:35<00:07, 1.16it/s]\n 84%|████████▍ | 42/50 [00:36<00:06, 1.16it/s]\n 86%|████████▌ | 43/50 [00:37<00:06, 1.17it/s]\n 88%|████████▊ | 44/50 [00:38<00:05, 1.17it/s]\n 90%|█████████ | 45/50 [00:38<00:04, 1.17it/s]\n 92%|█████████▏| 46/50 [00:39<00:03, 1.17it/s]\n 94%|█████████▍| 47/50 [00:40<00:02, 1.17it/s]\n 96%|█████████▌| 48/50 [00:41<00:01, 1.17it/s]\n 98%|█████████▊| 49/50 [00:42<00:00, 1.17it/s]\n100%|██████████| 50/50 [00:43<00:00, 1.17it/s]\n100%|██████████| 50/50 [00:43<00:00, 1.16it/s]", "metrics": { "predict_time": 49.753553, "total_time": 130.695147 }, "output": [ "https://replicate.delivery/pbxt/D45W1Jo8hbIlDVDxFGn8pfCe6Bryds8hQ6sStPqLR7fwgy0iA/out-0.png", "https://replicate.delivery/pbxt/tRZAasjnM977EBODtbZsf9jH51McmxH27exmzg0rqneygy0iA/out-1.png", "https://replicate.delivery/pbxt/gKxzgQ9AzIJfAS6kJG1pf34flQgAPacKo7Tt2kzMCmV0gy0iA/out-2.png", "https://replicate.delivery/pbxt/cI9FGWJxY6qZO1H4uvvbGSUGV3oxYmS0rc3q5X8snY8GUmWE/out-3.png" ], "started_at": "2023-08-15T20:36:58.012641Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/6rwhs6tbuli4mwqrdt7gxq3dou", "cancel": "https://api.replicate.com/v1/predictions/6rwhs6tbuli4mwqrdt7gxq3dou/cancel" }, "version": "3c39ca4c9c8c1b3f1a5839fe46319da49baafeabed07c0741f43ac70e874de54" }
Generated inUsing seed: 34562 Prompt: a night time landscape photo taken by <s0><s1>, blue pleiades, mountain, snow, astrophotography, beautiful, big sky txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:01<01:06, 1.35s/it] 4%|▍ | 2/50 [00:02<00:50, 1.06s/it] 6%|▌ | 3/50 [00:03<00:45, 1.04it/s] 8%|▊ | 4/50 [00:03<00:42, 1.08it/s] 10%|█ | 5/50 [00:04<00:40, 1.11it/s] 12%|█▏ | 6/50 [00:05<00:38, 1.13it/s] 14%|█▍ | 7/50 [00:06<00:37, 1.15it/s] 16%|█▌ | 8/50 [00:07<00:36, 1.16it/s] 18%|█▊ | 9/50 [00:08<00:35, 1.16it/s] 20%|██ | 10/50 [00:09<00:34, 1.17it/s] 22%|██▏ | 11/50 [00:09<00:33, 1.17it/s] 24%|██▍ | 12/50 [00:10<00:32, 1.17it/s] 26%|██▌ | 13/50 [00:11<00:31, 1.17it/s] 28%|██▊ | 14/50 [00:12<00:30, 1.17it/s] 30%|███ | 15/50 [00:13<00:29, 1.17it/s] 32%|███▏ | 16/50 [00:14<00:29, 1.17it/s] 34%|███▍ | 17/50 [00:14<00:28, 1.17it/s] 36%|███▌ | 18/50 [00:15<00:27, 1.17it/s] 38%|███▊ | 19/50 [00:16<00:26, 1.17it/s] 40%|████ | 20/50 [00:17<00:25, 1.17it/s] 42%|████▏ | 21/50 [00:18<00:24, 1.17it/s] 44%|████▍ | 22/50 [00:19<00:23, 1.17it/s] 46%|████▌ | 23/50 [00:20<00:23, 1.17it/s] 48%|████▊ | 24/50 [00:20<00:22, 1.17it/s] 50%|█████ | 25/50 [00:21<00:21, 1.17it/s] 52%|█████▏ | 26/50 [00:22<00:20, 1.17it/s] 54%|█████▍ | 27/50 [00:23<00:19, 1.17it/s] 56%|█████▌ | 28/50 [00:24<00:18, 1.17it/s] 58%|█████▊ | 29/50 [00:25<00:17, 1.17it/s] 60%|██████ | 30/50 [00:26<00:17, 1.17it/s] 62%|██████▏ | 31/50 [00:26<00:16, 1.17it/s] 64%|██████▍ | 32/50 [00:27<00:15, 1.17it/s] 66%|██████▌ | 33/50 [00:28<00:14, 1.17it/s] 68%|██████▊ | 34/50 [00:29<00:13, 1.17it/s] 70%|███████ | 35/50 [00:30<00:12, 1.17it/s] 72%|███████▏ | 36/50 [00:31<00:12, 1.17it/s] 74%|███████▍ | 37/50 [00:32<00:11, 1.17it/s] 76%|███████▌ | 38/50 [00:32<00:10, 1.17it/s] 78%|███████▊ | 39/50 [00:33<00:09, 1.17it/s] 80%|████████ | 40/50 [00:34<00:08, 1.16it/s] 82%|████████▏ | 41/50 [00:35<00:07, 1.16it/s] 84%|████████▍ | 42/50 [00:36<00:06, 1.16it/s] 86%|████████▌ | 43/50 [00:37<00:06, 1.17it/s] 88%|████████▊ | 44/50 [00:38<00:05, 1.17it/s] 90%|█████████ | 45/50 [00:38<00:04, 1.17it/s] 92%|█████████▏| 46/50 [00:39<00:03, 1.17it/s] 94%|█████████▍| 47/50 [00:40<00:02, 1.17it/s] 96%|█████████▌| 48/50 [00:41<00:01, 1.17it/s] 98%|█████████▊| 49/50 [00:42<00:00, 1.17it/s] 100%|██████████| 50/50 [00:43<00:00, 1.17it/s] 100%|██████████| 50/50 [00:43<00:00, 1.16it/s]
Prediction
fofr/sdxl-jwst:3c39ca4cIDc2zqatdbfwqoftfjgzf3fu4tpyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 768
- height
- 1152
- prompt
- a night time landscape photo taken by TOK, nebula, mountain, snow, astrophotography, beautiful, big sky
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.63
- num_outputs
- 4
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- milky way, daytime, garish
- prompt_strength
- 0.76
- num_inference_steps
- 50
{ "image": "https://replicate.delivery/pbxt/JMAnxvOX1aNZp4jWUMiV9DpdQZrbh8cKw1rEYN83ALER1L1r/fofr_purple_nebula_in_the_night_sky_above_snow_fields_in_the_st_313c5fa3-371e-4581-bc85-bc7cf07f0bab.png", "width": 768, "height": 1152, "prompt": "a night time landscape photo taken by TOK, nebula, mountain, snow, astrophotography, beautiful, big sky", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.63, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "milky way, daytime, garish", "prompt_strength": 0.76, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/sdxl-jwst using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-jwst:3c39ca4c9c8c1b3f1a5839fe46319da49baafeabed07c0741f43ac70e874de54", { input: { image: "https://replicate.delivery/pbxt/JMAnxvOX1aNZp4jWUMiV9DpdQZrbh8cKw1rEYN83ALER1L1r/fofr_purple_nebula_in_the_night_sky_above_snow_fields_in_the_st_313c5fa3-371e-4581-bc85-bc7cf07f0bab.png", width: 768, height: 1152, prompt: "a night time landscape photo taken by TOK, nebula, mountain, snow, astrophotography, beautiful, big sky", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.63, num_outputs: 4, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "milky way, daytime, garish", prompt_strength: 0.76, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client:import replicate
Run fofr/sdxl-jwst using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-jwst:3c39ca4c9c8c1b3f1a5839fe46319da49baafeabed07c0741f43ac70e874de54", input={ "image": "https://replicate.delivery/pbxt/JMAnxvOX1aNZp4jWUMiV9DpdQZrbh8cKw1rEYN83ALER1L1r/fofr_purple_nebula_in_the_night_sky_above_snow_fields_in_the_st_313c5fa3-371e-4581-bc85-bc7cf07f0bab.png", "width": 768, "height": 1152, "prompt": "a night time landscape photo taken by TOK, nebula, mountain, snow, astrophotography, beautiful, big sky", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.63, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "milky way, daytime, garish", "prompt_strength": 0.76, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/sdxl-jwst 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": "3c39ca4c9c8c1b3f1a5839fe46319da49baafeabed07c0741f43ac70e874de54", "input": { "image": "https://replicate.delivery/pbxt/JMAnxvOX1aNZp4jWUMiV9DpdQZrbh8cKw1rEYN83ALER1L1r/fofr_purple_nebula_in_the_night_sky_above_snow_fields_in_the_st_313c5fa3-371e-4581-bc85-bc7cf07f0bab.png", "width": 768, "height": 1152, "prompt": "a night time landscape photo taken by TOK, nebula, mountain, snow, astrophotography, beautiful, big sky", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.63, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "milky way, daytime, garish", "prompt_strength": 0.76, "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": "2023-08-15T21:44:01.043360Z", "created_at": "2023-08-15T21:42:20.353686Z", "data_removed": false, "error": null, "id": "c2zqatdbfwqoftfjgzf3fu4tpy", "input": { "image": "https://replicate.delivery/pbxt/JMAnxvOX1aNZp4jWUMiV9DpdQZrbh8cKw1rEYN83ALER1L1r/fofr_purple_nebula_in_the_night_sky_above_snow_fields_in_the_st_313c5fa3-371e-4581-bc85-bc7cf07f0bab.png", "width": 768, "height": 1152, "prompt": "a night time landscape photo taken by TOK, nebula, mountain, snow, astrophotography, beautiful, big sky", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.63, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "milky way, daytime, garish", "prompt_strength": 0.76, "num_inference_steps": 50 }, "logs": "Using seed: 58742\nPrompt: a night time landscape photo taken by <s0><s1>, nebula, mountain, snow, astrophotography, beautiful, big sky\nimg2img mode\n 0%| | 0/35 [00:00<?, ?it/s]\n 3%|▎ | 1/35 [00:01<00:38, 1.14s/it]\n 6%|▌ | 2/35 [00:02<00:37, 1.14s/it]\n 9%|▊ | 3/35 [00:03<00:36, 1.14s/it]\n 11%|█▏ | 4/35 [00:04<00:35, 1.14s/it]\n 14%|█▍ | 5/35 [00:05<00:34, 1.14s/it]\n 17%|█▋ | 6/35 [00:06<00:33, 1.14s/it]\n 20%|██ | 7/35 [00:08<00:31, 1.14s/it]\n 23%|██▎ | 8/35 [00:09<00:30, 1.14s/it]\n 26%|██▌ | 9/35 [00:10<00:29, 1.14s/it]\n 29%|██▊ | 10/35 [00:11<00:28, 1.14s/it]\n 31%|███▏ | 11/35 [00:12<00:27, 1.14s/it]\n 34%|███▍ | 12/35 [00:13<00:26, 1.14s/it]\n 37%|███▋ | 13/35 [00:14<00:25, 1.14s/it]\n 40%|████ | 14/35 [00:15<00:24, 1.14s/it]\n 43%|████▎ | 15/35 [00:17<00:22, 1.14s/it]\n 46%|████▌ | 16/35 [00:18<00:21, 1.14s/it]\n 49%|████▊ | 17/35 [00:19<00:20, 1.14s/it]\n 51%|█████▏ | 18/35 [00:20<00:19, 1.14s/it]\n 54%|█████▍ | 19/35 [00:21<00:18, 1.14s/it]\n 57%|█████▋ | 20/35 [00:22<00:17, 1.15s/it]\n 60%|██████ | 21/35 [00:24<00:16, 1.15s/it]\n 63%|██████▎ | 22/35 [00:25<00:14, 1.15s/it]\n 66%|██████▌ | 23/35 [00:26<00:13, 1.15s/it]\n 69%|██████▊ | 24/35 [00:27<00:12, 1.15s/it]\n 71%|███████▏ | 25/35 [00:28<00:11, 1.15s/it]\n 74%|███████▍ | 26/35 [00:29<00:10, 1.15s/it]\n 77%|███████▋ | 27/35 [00:30<00:09, 1.15s/it]\n 80%|████████ | 28/35 [00:32<00:08, 1.15s/it]\n 83%|████████▎ | 29/35 [00:33<00:06, 1.15s/it]\n 86%|████████▌ | 30/35 [00:34<00:05, 1.15s/it]\n 89%|████████▊ | 31/35 [00:35<00:04, 1.15s/it]\n 91%|█████████▏| 32/35 [00:36<00:03, 1.15s/it]\n 94%|█████████▍| 33/35 [00:37<00:02, 1.15s/it]\n 97%|█████████▋| 34/35 [00:38<00:01, 1.15s/it]\n100%|██████████| 35/35 [00:40<00:00, 1.15s/it]\n100%|██████████| 35/35 [00:40<00:00, 1.15s/it]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:01, 1.05it/s]\n 67%|██████▋ | 2/3 [00:01<00:00, 1.06it/s]\n100%|██████████| 3/3 [00:02<00:00, 1.06it/s]\n100%|██████████| 3/3 [00:02<00:00, 1.06it/s]", "metrics": { "predict_time": 50.201489, "total_time": 100.689674 }, "output": [ "https://replicate.delivery/pbxt/m4BSZZK6Kw7UA51VmWL4tdfCsqawZmyZ23XNf9ZD6Qee5opFB/out-0.png", "https://replicate.delivery/pbxt/YK7M4WUPZ2ZXDd95VlCk7rdePhZ4biSqNeZedtm83peC6opFB/out-1.png", "https://replicate.delivery/pbxt/q7groeJT9oWWI6VQBDrvpl6zKr2fdPCYVw5JPY25WgmgOaaRA/out-2.png", "https://replicate.delivery/pbxt/F8sRfwf8JriWoUoumzmYyfpMIvxsnzQF5bxTyzTWSwHBd00iA/out-3.png" ], "started_at": "2023-08-15T21:43:10.841871Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/c2zqatdbfwqoftfjgzf3fu4tpy", "cancel": "https://api.replicate.com/v1/predictions/c2zqatdbfwqoftfjgzf3fu4tpy/cancel" }, "version": "3c39ca4c9c8c1b3f1a5839fe46319da49baafeabed07c0741f43ac70e874de54" }
Generated inUsing seed: 58742 Prompt: a night time landscape photo taken by <s0><s1>, nebula, mountain, snow, astrophotography, beautiful, big sky img2img mode 0%| | 0/35 [00:00<?, ?it/s] 3%|▎ | 1/35 [00:01<00:38, 1.14s/it] 6%|▌ | 2/35 [00:02<00:37, 1.14s/it] 9%|▊ | 3/35 [00:03<00:36, 1.14s/it] 11%|█▏ | 4/35 [00:04<00:35, 1.14s/it] 14%|█▍ | 5/35 [00:05<00:34, 1.14s/it] 17%|█▋ | 6/35 [00:06<00:33, 1.14s/it] 20%|██ | 7/35 [00:08<00:31, 1.14s/it] 23%|██▎ | 8/35 [00:09<00:30, 1.14s/it] 26%|██▌ | 9/35 [00:10<00:29, 1.14s/it] 29%|██▊ | 10/35 [00:11<00:28, 1.14s/it] 31%|███▏ | 11/35 [00:12<00:27, 1.14s/it] 34%|███▍ | 12/35 [00:13<00:26, 1.14s/it] 37%|███▋ | 13/35 [00:14<00:25, 1.14s/it] 40%|████ | 14/35 [00:15<00:24, 1.14s/it] 43%|████▎ | 15/35 [00:17<00:22, 1.14s/it] 46%|████▌ | 16/35 [00:18<00:21, 1.14s/it] 49%|████▊ | 17/35 [00:19<00:20, 1.14s/it] 51%|█████▏ | 18/35 [00:20<00:19, 1.14s/it] 54%|█████▍ | 19/35 [00:21<00:18, 1.14s/it] 57%|█████▋ | 20/35 [00:22<00:17, 1.15s/it] 60%|██████ | 21/35 [00:24<00:16, 1.15s/it] 63%|██████▎ | 22/35 [00:25<00:14, 1.15s/it] 66%|██████▌ | 23/35 [00:26<00:13, 1.15s/it] 69%|██████▊ | 24/35 [00:27<00:12, 1.15s/it] 71%|███████▏ | 25/35 [00:28<00:11, 1.15s/it] 74%|███████▍ | 26/35 [00:29<00:10, 1.15s/it] 77%|███████▋ | 27/35 [00:30<00:09, 1.15s/it] 80%|████████ | 28/35 [00:32<00:08, 1.15s/it] 83%|████████▎ | 29/35 [00:33<00:06, 1.15s/it] 86%|████████▌ | 30/35 [00:34<00:05, 1.15s/it] 89%|████████▊ | 31/35 [00:35<00:04, 1.15s/it] 91%|█████████▏| 32/35 [00:36<00:03, 1.15s/it] 94%|█████████▍| 33/35 [00:37<00:02, 1.15s/it] 97%|█████████▋| 34/35 [00:38<00:01, 1.15s/it] 100%|██████████| 35/35 [00:40<00:00, 1.15s/it] 100%|██████████| 35/35 [00:40<00:00, 1.15s/it] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:01, 1.05it/s] 67%|██████▋ | 2/3 [00:01<00:00, 1.06it/s] 100%|██████████| 3/3 [00:02<00:00, 1.06it/s] 100%|██████████| 3/3 [00:02<00:00, 1.06it/s]
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