anotherjesse / streaming-sdxl
stream previews as it is generated
- Public
- 686 runs
-
L40S
Prediction
anotherjesse/streaming-sdxl:342f66e96ce05221d91654ab7479593a3e0554004e502d5c3e28cc84fa0b0245IDezpvhitbro5zgiugi7wzx5kv2yStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- An astronaut riding a rainbow unicorn
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- preview_steps
- 5
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "An astronaut riding a rainbow unicorn", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "preview_steps": 5, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run anotherjesse/streaming-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "anotherjesse/streaming-sdxl:342f66e96ce05221d91654ab7479593a3e0554004e502d5c3e28cc84fa0b0245", { input: { width: 1024, height: 1024, prompt: "An astronaut riding a rainbow unicorn", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, preview_steps: 5, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "", 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 replicateImport the client:import replicateRun anotherjesse/streaming-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "anotherjesse/streaming-sdxl:342f66e96ce05221d91654ab7479593a3e0554004e502d5c3e28cc84fa0b0245", input={ "width": 1024, "height": 1024, "prompt": "An astronaut riding a rainbow unicorn", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "preview_steps": 5, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } ) # The anotherjesse/streaming-sdxl model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/anotherjesse/streaming-sdxl/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run anotherjesse/streaming-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": "anotherjesse/streaming-sdxl:342f66e96ce05221d91654ab7479593a3e0554004e502d5c3e28cc84fa0b0245", "input": { "width": 1024, "height": 1024, "prompt": "An astronaut riding a rainbow unicorn", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "preview_steps": 5, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-13T22:51:39.972594Z", "created_at": "2023-09-13T22:51:26.023554Z", "data_removed": false, "error": null, "id": "ezpvhitbro5zgiugi7wzx5kv2y", "input": { "width": 1024, "height": 1024, "prompt": "An astronaut riding a rainbow unicorn", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "preview_steps": 5, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 36830\nPrompt: An astronaut riding a rainbow unicorn\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\nyielding latents\n 2%|▏ | 1/50 [00:00<00:09, 4.97it/s]\n 4%|▍ | 2/50 [00:00<00:16, 2.85it/s]\n 6%|▌ | 3/50 [00:00<00:13, 3.54it/s]\n 8%|▊ | 4/50 [00:01<00:11, 3.99it/s]\n 10%|█ | 5/50 [00:01<00:10, 4.28it/s]\nyielding latents\n 12%|█▏ | 6/50 [00:01<00:09, 4.48it/s]\n 14%|█▍ | 7/50 [00:01<00:12, 3.38it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.76it/s]\n 18%|█▊ | 9/50 [00:02<00:10, 4.07it/s]\n 20%|██ | 10/50 [00:02<00:09, 4.29it/s]\nyielding latents\n 22%|██▏ | 11/50 [00:02<00:08, 4.47it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.46it/s]\n 26%|██▌ | 13/50 [00:03<00:09, 3.80it/s]\n 28%|██▊ | 14/50 [00:03<00:08, 4.09it/s]\n 30%|███ | 15/50 [00:03<00:08, 4.32it/s]\nyielding latents\n 32%|███▏ | 16/50 [00:03<00:07, 4.45it/s]\n 34%|███▍ | 17/50 [00:04<00:10, 3.29it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.65it/s]\n 38%|███▊ | 19/50 [00:04<00:07, 3.96it/s]\n 40%|████ | 20/50 [00:05<00:07, 4.20it/s]\nyielding latents\n 42%|████▏ | 21/50 [00:05<00:06, 4.38it/s]\n 44%|████▍ | 22/50 [00:05<00:08, 3.26it/s]\n 46%|████▌ | 23/50 [00:05<00:07, 3.63it/s]\n 48%|████▊ | 24/50 [00:06<00:06, 3.94it/s]\n 50%|█████ | 25/50 [00:06<00:05, 4.19it/s]\nyielding latents\n 52%|█████▏ | 26/50 [00:06<00:05, 4.38it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.40it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.74it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 4.03it/s]\n 60%|██████ | 30/50 [00:07<00:04, 4.26it/s]\nyielding latents\n 62%|██████▏ | 31/50 [00:07<00:04, 4.43it/s]\n 64%|██████▍ | 32/50 [00:08<00:05, 3.45it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.79it/s]\n 68%|██████▊ | 34/50 [00:08<00:03, 4.06it/s]\n 70%|███████ | 35/50 [00:08<00:03, 4.28it/s]\nyielding latents\n 72%|███████▏ | 36/50 [00:09<00:03, 4.45it/s]\n 74%|███████▍ | 37/50 [00:09<00:03, 3.43it/s]\n 76%|███████▌ | 38/50 [00:09<00:03, 3.77it/s]\n 78%|███████▊ | 39/50 [00:09<00:02, 4.05it/s]\n 80%|████████ | 40/50 [00:10<00:02, 4.27it/s]\nyielding latents\n 82%|████████▏ | 41/50 [00:10<00:02, 4.44it/s]\n 84%|████████▍ | 42/50 [00:10<00:02, 3.44it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.78it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 4.06it/s]\n 90%|█████████ | 45/50 [00:11<00:01, 4.28it/s]\nyielding latents\n 92%|█████████▏| 46/50 [00:11<00:00, 4.45it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.45it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.79it/s]\n 98%|█████████▊| 49/50 [00:12<00:00, 4.07it/s]\n100%|██████████| 50/50 [00:12<00:00, 4.29it/s]\n100%|██████████| 50/50 [00:12<00:00, 3.94it/s]", "metrics": { "predict_time": 13.983038, "total_time": 13.94904 }, "output": [ "https://pbxt.replicate.delivery/kW8fAcvc6KyKSqXAx2GXY72W7yVRFczm5uPJGHIL8wZ3dfjRA/0000.jpg", "https://pbxt.replicate.delivery/JZxWZi0P5SZFN5gnFu4Vop20XFGlG4DztdNDCJO8pfw3dfjRA/0005.jpg", "https://pbxt.replicate.delivery/XSojnlcTcJ5iBNaQ4ftDuC1OQEmeMp4NYFa01eYAFosi39HjA/0010.jpg", "https://pbxt.replicate.delivery/5JUydfceTosdAkePUmIMcbIVBZYBcigTrWrB2sjsLNDl39HjA/0015.jpg", "https://pbxt.replicate.delivery/5WIMaXF4XQIFO1uTSvc7tTjsDEQuOeVFXYJqRIrrXPn5dfjRA/0020.jpg", "https://pbxt.replicate.delivery/g3O1iks3we34MSkOgmBWjAGJsekOzTUeCrTw9bjbaeKXv7PGB/0025.jpg", "https://pbxt.replicate.delivery/tWRQcYcHIApAERLcG2gn0S5znCfcqtdoOevVbaUJ8ct27eHjA/0030.jpg", "https://pbxt.replicate.delivery/bzSZnPxdkS7nHZaDT60QXN9GxvNO77z0fXoFi6oH7Bx7dfjRA/0035.jpg", "https://pbxt.replicate.delivery/ajx1LpNLcH5dPNbe8jFscGijwN0t8afuKgOakBiDCxX47eHjA/0040.jpg", "https://pbxt.replicate.delivery/a8BBeeGfbZCbnJk8EV2gdNEYPeYE94dWBiJ2KeYC2VZVfufxIA/0045.jpg", "https://pbxt.replicate.delivery/kht9VnpIDnaBAJa4i2bHAHob7ruWXWDvJTderc7Mzb59dfjRA/results.png" ], "started_at": "2023-09-13T22:51:25.989556Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ezpvhitbro5zgiugi7wzx5kv2y", "cancel": "https://api.replicate.com/v1/predictions/ezpvhitbro5zgiugi7wzx5kv2y/cancel" }, "version": "342f66e96ce05221d91654ab7479593a3e0554004e502d5c3e28cc84fa0b0245" }Generated inUsing seed: 36830 Prompt: An astronaut riding a rainbow unicorn txt2img mode 0%| | 0/50 [00:00<?, ?it/s] yielding latents 2%|▏ | 1/50 [00:00<00:09, 4.97it/s] 4%|▍ | 2/50 [00:00<00:16, 2.85it/s] 6%|▌ | 3/50 [00:00<00:13, 3.54it/s] 8%|▊ | 4/50 [00:01<00:11, 3.99it/s] 10%|█ | 5/50 [00:01<00:10, 4.28it/s] yielding latents 12%|█▏ | 6/50 [00:01<00:09, 4.48it/s] 14%|█▍ | 7/50 [00:01<00:12, 3.38it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.76it/s] 18%|█▊ | 9/50 [00:02<00:10, 4.07it/s] 20%|██ | 10/50 [00:02<00:09, 4.29it/s] yielding latents 22%|██▏ | 11/50 [00:02<00:08, 4.47it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.46it/s] 26%|██▌ | 13/50 [00:03<00:09, 3.80it/s] 28%|██▊ | 14/50 [00:03<00:08, 4.09it/s] 30%|███ | 15/50 [00:03<00:08, 4.32it/s] yielding latents 32%|███▏ | 16/50 [00:03<00:07, 4.45it/s] 34%|███▍ | 17/50 [00:04<00:10, 3.29it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.65it/s] 38%|███▊ | 19/50 [00:04<00:07, 3.96it/s] 40%|████ | 20/50 [00:05<00:07, 4.20it/s] yielding latents 42%|████▏ | 21/50 [00:05<00:06, 4.38it/s] 44%|████▍ | 22/50 [00:05<00:08, 3.26it/s] 46%|████▌ | 23/50 [00:05<00:07, 3.63it/s] 48%|████▊ | 24/50 [00:06<00:06, 3.94it/s] 50%|█████ | 25/50 [00:06<00:05, 4.19it/s] yielding latents 52%|█████▏ | 26/50 [00:06<00:05, 4.38it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.40it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.74it/s] 58%|█████▊ | 29/50 [00:07<00:05, 4.03it/s] 60%|██████ | 30/50 [00:07<00:04, 4.26it/s] yielding latents 62%|██████▏ | 31/50 [00:07<00:04, 4.43it/s] 64%|██████▍ | 32/50 [00:08<00:05, 3.45it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.79it/s] 68%|██████▊ | 34/50 [00:08<00:03, 4.06it/s] 70%|███████ | 35/50 [00:08<00:03, 4.28it/s] yielding latents 72%|███████▏ | 36/50 [00:09<00:03, 4.45it/s] 74%|███████▍ | 37/50 [00:09<00:03, 3.43it/s] 76%|███████▌ | 38/50 [00:09<00:03, 3.77it/s] 78%|███████▊ | 39/50 [00:09<00:02, 4.05it/s] 80%|████████ | 40/50 [00:10<00:02, 4.27it/s] yielding latents 82%|████████▏ | 41/50 [00:10<00:02, 4.44it/s] 84%|████████▍ | 42/50 [00:10<00:02, 3.44it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.78it/s] 88%|████████▊ | 44/50 [00:11<00:01, 4.06it/s] 90%|█████████ | 45/50 [00:11<00:01, 4.28it/s] yielding latents 92%|█████████▏| 46/50 [00:11<00:00, 4.45it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.45it/s] 96%|█████████▌| 48/50 [00:12<00:00, 3.79it/s] 98%|█████████▊| 49/50 [00:12<00:00, 4.07it/s] 100%|██████████| 50/50 [00:12<00:00, 4.29it/s] 100%|██████████| 50/50 [00:12<00:00, 3.94it/s]
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