Prediction
georgedavila/sdxl-beethoven-spectrograms-lora:193c41eaa2f90912bb886b75950af5d433eb9e6007c17507e5da11e527ad38e5ID
q38mneyzm1rgm0cfrmfva99c7c
Status
Succeeded
Source
Web
Hardware
A40 (Large)
Total duration
Created
Input
- myprompt
- A SPECTROGRAM image
- outWidth
- 1024
- outHeight
- 1024
- lora_scale
- 0.6
- num_outputs
- 1
- guidanceScale
- 7.5
- promptAddendum
- high_noise_frac
- 0.8
- num_inference_steps
- 50
{
"myprompt": "A SPECTROGRAM image",
"outWidth": 1024,
"outHeight": 1024,
"lora_scale": 0.6,
"num_outputs": 1,
"guidanceScale": 7.5,
"promptAddendum": "",
"high_noise_frac": 0.8,
"num_inference_steps": 50
}Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_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";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run georgedavila/sdxl-beethoven-spectrograms-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"georgedavila/sdxl-beethoven-spectrograms-lora:193c41eaa2f90912bb886b75950af5d433eb9e6007c17507e5da11e527ad38e5",
{
input: {
myprompt: "A SPECTROGRAM image",
outWidth: 1024,
outHeight: 1024,
lora_scale: 0.6,
num_outputs: 1,
guidanceScale: 7.5,
promptAddendum: "",
high_noise_frac: 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 replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun georgedavila/sdxl-beethoven-spectrograms-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"georgedavila/sdxl-beethoven-spectrograms-lora:193c41eaa2f90912bb886b75950af5d433eb9e6007c17507e5da11e527ad38e5",
input={
"myprompt": "A SPECTROGRAM image",
"outWidth": 1024,
"outHeight": 1024,
"lora_scale": 0.6,
"num_outputs": 1,
"guidanceScale": 7.5,
"promptAddendum": "",
"high_noise_frac": 0.8,
"num_inference_steps": 50
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run georgedavila/sdxl-beethoven-spectrograms-lora 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": "georgedavila/sdxl-beethoven-spectrograms-lora:193c41eaa2f90912bb886b75950af5d433eb9e6007c17507e5da11e527ad38e5",
"input": {
"myprompt": "A SPECTROGRAM image",
"outWidth": 1024,
"outHeight": 1024,
"lora_scale": 0.6,
"num_outputs": 1,
"guidanceScale": 7.5,
"promptAddendum": "",
"high_noise_frac": 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": "2024-05-29T16:14:09.349554Z",
"created_at": "2024-05-29T16:12:31.520000Z",
"data_removed": false,
"error": null,
"id": "q38mneyzm1rgm0cfrmfva99c7c",
"input": {
"myprompt": "A SPECTROGRAM image",
"outWidth": 1024,
"outHeight": 1024,
"lora_scale": 0.6,
"num_outputs": 1,
"guidanceScale": 7.5,
"promptAddendum": "",
"high_noise_frac": 0.8,
"num_inference_steps": 50
},
"logs": "Using seed: 9964\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:16, 2.93it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.60it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.87it/s]\n 8%|▊ | 4/50 [00:01<00:11, 4.02it/s]\n 10%|█ | 5/50 [00:01<00:10, 4.10it/s]\n 12%|█▏ | 6/50 [00:01<00:10, 4.15it/s]\n 14%|█▍ | 7/50 [00:01<00:10, 4.18it/s]\n 16%|█▌ | 8/50 [00:01<00:09, 4.20it/s]\n 18%|█▊ | 9/50 [00:02<00:09, 4.22it/s]\n 20%|██ | 10/50 [00:02<00:09, 4.22it/s]\n 22%|██▏ | 11/50 [00:02<00:09, 4.23it/s]\n 24%|██▍ | 12/50 [00:02<00:08, 4.23it/s]\n 26%|██▌ | 13/50 [00:03<00:08, 4.24it/s]\n 28%|██▊ | 14/50 [00:03<00:08, 4.24it/s]\n 30%|███ | 15/50 [00:03<00:08, 4.24it/s]\n 32%|███▏ | 16/50 [00:03<00:08, 4.24it/s]\n 34%|███▍ | 17/50 [00:04<00:07, 4.24it/s]\n 36%|███▌ | 18/50 [00:04<00:07, 4.24it/s]\n 38%|███▊ | 19/50 [00:04<00:07, 4.24it/s]\n 40%|████ | 20/50 [00:04<00:07, 4.24it/s]\n 42%|████▏ | 21/50 [00:05<00:06, 4.24it/s]\n 44%|████▍ | 22/50 [00:05<00:06, 4.24it/s]\n 46%|████▌ | 23/50 [00:05<00:06, 4.24it/s]\n 48%|████▊ | 24/50 [00:05<00:06, 4.24it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.24it/s]\n 52%|█████▏ | 26/50 [00:06<00:05, 4.25it/s]\n 54%|█████▍ | 27/50 [00:06<00:05, 4.26it/s]\n 56%|█████▌ | 28/50 [00:06<00:05, 4.26it/s]\n 58%|█████▊ | 29/50 [00:06<00:04, 4.26it/s]\n 60%|██████ | 30/50 [00:07<00:04, 4.27it/s]\n 62%|██████▏ | 31/50 [00:07<00:04, 4.27it/s]\n 64%|██████▍ | 32/50 [00:07<00:04, 4.27it/s]\n 66%|██████▌ | 33/50 [00:07<00:03, 4.27it/s]\n 68%|██████▊ | 34/50 [00:08<00:03, 4.26it/s]\n 70%|███████ | 35/50 [00:08<00:03, 4.26it/s]\n 72%|███████▏ | 36/50 [00:08<00:03, 4.26it/s]\n 74%|███████▍ | 37/50 [00:08<00:03, 4.26it/s]\n 76%|███████▌ | 38/50 [00:09<00:02, 4.26it/s]\n 78%|███████▊ | 39/50 [00:09<00:02, 4.26it/s]\n 80%|████████ | 40/50 [00:09<00:02, 4.26it/s]\n 82%|████████▏ | 41/50 [00:09<00:02, 4.26it/s]\n 84%|████████▍ | 42/50 [00:09<00:01, 4.26it/s]\n 86%|████████▌ | 43/50 [00:10<00:01, 4.26it/s]\n 88%|████████▊ | 44/50 [00:10<00:01, 4.25it/s]\n 90%|█████████ | 45/50 [00:10<00:01, 4.25it/s]\n 92%|█████████▏| 46/50 [00:10<00:00, 4.25it/s]\n 94%|█████████▍| 47/50 [00:11<00:00, 4.25it/s]\n 96%|█████████▌| 48/50 [00:11<00:00, 4.25it/s]\n 98%|█████████▊| 49/50 [00:11<00:00, 4.25it/s]\n100%|██████████| 50/50 [00:11<00:00, 4.26it/s]\n100%|██████████| 50/50 [00:11<00:00, 4.22it/s]",
"metrics": {
"predict_time": 14.871608,
"total_time": 97.829554
},
"output": [
"https://replicate.delivery/pbxt/Y9Owe7ENpI12VKYDUNnwWLJXaem0mNHVhflfrqJbjoF9kBlLB/out-0.png"
],
"started_at": "2024-05-29T16:13:54.477946Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/q38mneyzm1rgm0cfrmfva99c7c",
"cancel": "https://api.replicate.com/v1/predictions/q38mneyzm1rgm0cfrmfva99c7c/cancel"
},
"version": "193c41eaa2f90912bb886b75950af5d433eb9e6007c17507e5da11e527ad38e5"
}Generated in
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