Prediction
stability-ai/sdxl:c221b2b8ID
dzsqmb3bg4lqpjkz2iptjqgccm
Status
Succeeded
Source
Web
Hardware
A40 (Large)
Total duration
Created
by @fofr
Input
- width
- 768
- height
- 768
- prompt
- An astronaut riding a rainbow unicorn, cinematic, dramatic
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 25
{
"width": 768,
"height": 768,
"prompt": "An astronaut riding a rainbow unicorn, cinematic, dramatic",
"refine": "expert_ensemble_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": false,
"high_noise_frac": 0.8,
"negative_prompt": "",
"prompt_strength": 0.8,
"num_inference_steps": 25
}
npm install replicate
Set the
REPLICATE_API_TOKEN
environment variableexport 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 stability-ai/sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"stability-ai/sdxl:c221b2b8ef527988fb59bf24a8b97c4561f1c671f73bd389f866bfb27c061316",
{
input: {
width: 768,
height: 768,
prompt: "An astronaut riding a rainbow unicorn, cinematic, dramatic",
refine: "expert_ensemble_refiner",
scheduler: "K_EULER",
lora_scale: 0.6,
num_outputs: 1,
guidance_scale: 7.5,
apply_watermark: false,
high_noise_frac: 0.8,
negative_prompt: "",
prompt_strength: 0.8,
num_inference_steps: 25
}
}
);
console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set the
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client
import replicate
Run stability-ai/sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"stability-ai/sdxl:c221b2b8ef527988fb59bf24a8b97c4561f1c671f73bd389f866bfb27c061316",
input={
"width": 768,
"height": 768,
"prompt": "An astronaut riding a rainbow unicorn, cinematic, dramatic",
"refine": "expert_ensemble_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": False,
"high_noise_frac": 0.8,
"negative_prompt": "",
"prompt_strength": 0.8,
"num_inference_steps": 25
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run stability-ai/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": "c221b2b8ef527988fb59bf24a8b97c4561f1c671f73bd389f866bfb27c061316",
"input": {
"width": 768,
"height": 768,
"prompt": "An astronaut riding a rainbow unicorn, cinematic, dramatic",
"refine": "expert_ensemble_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": false,
"high_noise_frac": 0.8,
"negative_prompt": "",
"prompt_strength": 0.8,
"num_inference_steps": 25
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{
"completed_at": "2023-10-12T17:10:12.909279Z",
"created_at": "2023-10-12T17:10:07.956869Z",
"data_removed": false,
"error": null,
"id": "dzsqmb3bg4lqpjkz2iptjqgccm",
"input": {
"width": 768,
"height": 768,
"prompt": "An astronaut riding a rainbow unicorn, cinematic, dramatic",
"refine": "expert_ensemble_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": false,
"high_noise_frac": 0.8,
"negative_prompt": "",
"prompt_strength": 0.8,
"num_inference_steps": 25
},
"logs": "Using seed: 16010\nPrompt: An astronaut riding a rainbow unicorn, cinematic, dramatic\ntxt2img mode\n 0%| | 0/16 [00:00<?, ?it/s]\n 6%|▋ | 1/16 [00:00<00:01, 7.96it/s]\n 12%|█▎ | 2/16 [00:00<00:01, 7.89it/s]\n 19%|█▉ | 3/16 [00:00<00:01, 7.86it/s]\n 25%|██▌ | 4/16 [00:00<00:01, 7.85it/s]\n 31%|███▏ | 5/16 [00:00<00:01, 7.83it/s]\n 38%|███▊ | 6/16 [00:00<00:01, 7.82it/s]\n 44%|████▍ | 7/16 [00:00<00:01, 7.81it/s]\n 50%|█████ | 8/16 [00:01<00:01, 7.80it/s]\n 56%|█████▋ | 9/16 [00:01<00:00, 7.80it/s]\n 62%|██████▎ | 10/16 [00:01<00:00, 7.78it/s]\n 69%|██████▉ | 11/16 [00:01<00:00, 7.79it/s]\n 75%|███████▌ | 12/16 [00:01<00:00, 7.79it/s]\n 81%|████████▏ | 13/16 [00:01<00:00, 7.78it/s]\n 88%|████████▊ | 14/16 [00:01<00:00, 7.79it/s]\n 94%|█████████▍| 15/16 [00:01<00:00, 7.79it/s]\n100%|██████████| 16/16 [00:02<00:00, 7.79it/s]\n100%|██████████| 16/16 [00:02<00:00, 7.81it/s]\n 0%| | 0/5 [00:00<?, ?it/s]\n 20%|██ | 1/5 [00:00<00:00, 7.47it/s]\n 40%|████ | 2/5 [00:00<00:00, 7.42it/s]\n 60%|██████ | 3/5 [00:00<00:00, 7.40it/s]\n 80%|████████ | 4/5 [00:00<00:00, 7.39it/s]\n100%|██████████| 5/5 [00:00<00:00, 7.39it/s]\n100%|██████████| 5/5 [00:00<00:00, 7.40it/s]",
"metrics": {
"predict_time": 4.981337,
"total_time": 4.95241
},
"output": [
"https://pbxt.replicate.delivery/YXbcLudoHBIYHV6L0HbcTx5iRzLFMwygLr3vhGpZI35caXbE/out-0.png"
],
"started_at": "2023-10-12T17:10:07.927942Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/dzsqmb3bg4lqpjkz2iptjqgccm",
"cancel": "https://api.replicate.com/v1/predictions/dzsqmb3bg4lqpjkz2iptjqgccm/cancel"
},
"version": "c221b2b8ef527988fb59bf24a8b97c4561f1c671f73bd389f866bfb27c061316"
}
Generated in
Using seed: 16010
Prompt: An astronaut riding a rainbow unicorn, cinematic, dramatic
txt2img mode
0%| | 0/16 [00:00<?, ?it/s]
6%|▋ | 1/16 [00:00<00:01, 7.96it/s]
12%|█▎ | 2/16 [00:00<00:01, 7.89it/s]
19%|█▉ | 3/16 [00:00<00:01, 7.86it/s]
25%|██▌ | 4/16 [00:00<00:01, 7.85it/s]
31%|███▏ | 5/16 [00:00<00:01, 7.83it/s]
38%|███▊ | 6/16 [00:00<00:01, 7.82it/s]
44%|████▍ | 7/16 [00:00<00:01, 7.81it/s]
50%|█████ | 8/16 [00:01<00:01, 7.80it/s]
56%|█████▋ | 9/16 [00:01<00:00, 7.80it/s]
62%|██████▎ | 10/16 [00:01<00:00, 7.78it/s]
69%|██████▉ | 11/16 [00:01<00:00, 7.79it/s]
75%|███████▌ | 12/16 [00:01<00:00, 7.79it/s]
81%|████████▏ | 13/16 [00:01<00:00, 7.78it/s]
88%|████████▊ | 14/16 [00:01<00:00, 7.79it/s]
94%|█████████▍| 15/16 [00:01<00:00, 7.79it/s]
100%|██████████| 16/16 [00:02<00:00, 7.79it/s]
100%|██████████| 16/16 [00:02<00:00, 7.81it/s]
0%| | 0/5 [00:00<?, ?it/s]
20%|██ | 1/5 [00:00<00:00, 7.47it/s]
40%|████ | 2/5 [00:00<00:00, 7.42it/s]
60%|██████ | 3/5 [00:00<00:00, 7.40it/s]
80%|████████ | 4/5 [00:00<00:00, 7.39it/s]
100%|██████████| 5/5 [00:00<00:00, 7.39it/s]
100%|██████████| 5/5 [00:00<00:00, 7.40it/s]