Prediction
cjwbw/sd-textual-inversion-ugly-sonic:57d8c937dead2f8437b8c93e586fa8dec20841dfdfc63ff5b4719ee8b867d483ID
lhd5ocvcubgtfbqemc67xqs3ue
Status
Succeeded
Source
Web
Hardware
–
Total duration
Created
Input
- prompt
- a beautiful portrait of [[[<ugly-sonic>]]] by Leonardo Da Vinci, (((painting, oil on canvas)))
- num_outputs
- 1
- guidance_scale
- 7.5
- num_inference_steps
- 50
{
"prompt": "a beautiful portrait of [[[<ugly-sonic>]]] by Leonardo Da Vinci, (((painting, oil on canvas)))",
"num_outputs": 1,
"guidance_scale": 7.5,
"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 cjwbw/sd-textual-inversion-ugly-sonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"cjwbw/sd-textual-inversion-ugly-sonic:57d8c937dead2f8437b8c93e586fa8dec20841dfdfc63ff5b4719ee8b867d483",
{
input: {
prompt: "a beautiful portrait of [[[<ugly-sonic>]]] by Leonardo Da Vinci, (((painting, oil on canvas)))",
num_outputs: 1,
guidance_scale: 7.5,
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 cjwbw/sd-textual-inversion-ugly-sonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"cjwbw/sd-textual-inversion-ugly-sonic:57d8c937dead2f8437b8c93e586fa8dec20841dfdfc63ff5b4719ee8b867d483",
input={
"prompt": "a beautiful portrait of [[[<ugly-sonic>]]] by Leonardo Da Vinci, (((painting, oil on canvas)))",
"num_outputs": 1,
"guidance_scale": 7.5,
"num_inference_steps": 50
}
)
# To access the file URL:
print(output[0].url())
#=> "http://example.com"
# To write the file to disk:
with open("my-image.png", "wb") as file:
file.write(output[0].read())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 cjwbw/sd-textual-inversion-ugly-sonic 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": "cjwbw/sd-textual-inversion-ugly-sonic:57d8c937dead2f8437b8c93e586fa8dec20841dfdfc63ff5b4719ee8b867d483",
"input": {
"prompt": "a beautiful portrait of [[[<ugly-sonic>]]] by Leonardo Da Vinci, (((painting, oil on canvas)))",
"num_outputs": 1,
"guidance_scale": 7.5,
"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": "2022-09-19T20:41:36.434355Z",
"created_at": "2022-09-19T20:41:11.488251Z",
"data_removed": false,
"error": null,
"id": "lhd5ocvcubgtfbqemc67xqs3ue",
"input": {
"prompt": "a beautiful portrait of [[[<ugly-sonic>]]] by Leonardo Da Vinci, (((painting, oil on canvas)))",
"num_outputs": 1,
"guidance_scale": 7.5,
"num_inference_steps": 50
},
"logs": "Using seed: 939\nGlobal seed set to 939\n\n 0%| | 0/51 [00:00<?, ?it/s]\n 2%|▏ | 1/51 [00:00<00:05, 8.55it/s]\n 4%|▍ | 2/51 [00:00<00:10, 4.76it/s]\n 6%|▌ | 3/51 [00:00<00:11, 4.15it/s]\n 8%|▊ | 4/51 [00:00<00:12, 3.80it/s]\n 10%|▉ | 5/51 [00:01<00:12, 3.73it/s]\n 12%|█▏ | 6/51 [00:01<00:12, 3.70it/s]\n 14%|█▎ | 7/51 [00:01<00:11, 3.67it/s]\n 16%|█▌ | 8/51 [00:02<00:11, 3.60it/s]\n 18%|█▊ | 9/51 [00:02<00:11, 3.60it/s]\n 20%|█▉ | 10/51 [00:02<00:11, 3.60it/s]\n 22%|██▏ | 11/51 [00:02<00:11, 3.58it/s]\n 24%|██▎ | 12/51 [00:03<00:10, 3.55it/s]\n 25%|██▌ | 13/51 [00:03<00:10, 3.56it/s]\n 27%|██▋ | 14/51 [00:03<00:10, 3.58it/s]\n 29%|██▉ | 15/51 [00:04<00:10, 3.55it/s]\n 31%|███▏ | 16/51 [00:04<00:09, 3.54it/s]\n 33%|███▎ | 17/51 [00:04<00:09, 3.54it/s]\n 35%|███▌ | 18/51 [00:04<00:09, 3.54it/s]\n 37%|███▋ | 19/51 [00:05<00:09, 3.52it/s]\n 39%|███▉ | 20/51 [00:05<00:08, 3.52it/s]\n 41%|████ | 21/51 [00:05<00:08, 3.54it/s]\n 43%|████▎ | 22/51 [00:06<00:08, 3.52it/s]\n 45%|████▌ | 23/51 [00:06<00:07, 3.52it/s]\n 47%|████▋ | 24/51 [00:06<00:07, 3.54it/s]\n 49%|████▉ | 25/51 [00:06<00:07, 3.54it/s]\n 51%|█████ | 26/51 [00:07<00:07, 3.53it/s]\n 53%|█████▎ | 27/51 [00:07<00:06, 3.52it/s]\n 55%|█████▍ | 28/51 [00:07<00:06, 3.52it/s]\n 57%|█████▋ | 29/51 [00:08<00:06, 3.51it/s]\n 59%|█████▉ | 30/51 [00:08<00:05, 3.51it/s]\n 61%|██████ | 31/51 [00:08<00:05, 3.51it/s]\n 63%|██████▎ | 32/51 [00:08<00:05, 3.51it/s]\n 65%|██████▍ | 33/51 [00:09<00:05, 3.52it/s]\n 67%|██████▋ | 34/51 [00:09<00:04, 3.52it/s]\n 69%|██████▊ | 35/51 [00:09<00:04, 3.52it/s]\n 71%|███████ | 36/51 [00:10<00:04, 3.52it/s]\n 73%|███████▎ | 37/51 [00:10<00:03, 3.52it/s]\n 75%|███████▍ | 38/51 [00:10<00:03, 3.52it/s]\n 76%|███████▋ | 39/51 [00:10<00:03, 3.52it/s]\n 78%|███████▊ | 40/51 [00:11<00:03, 3.51it/s]\n 80%|████████ | 41/51 [00:11<00:02, 3.49it/s]\n 82%|████████▏ | 42/51 [00:11<00:02, 3.49it/s]\n 84%|████████▍ | 43/51 [00:12<00:02, 3.48it/s]\n 86%|████████▋ | 44/51 [00:12<00:02, 3.49it/s]\n 88%|████████▊ | 45/51 [00:12<00:01, 3.50it/s]\n 90%|█████████ | 46/51 [00:12<00:01, 3.50it/s]\n 92%|█████████▏| 47/51 [00:13<00:01, 3.50it/s]\n 94%|█████████▍| 48/51 [00:13<00:00, 3.48it/s]\n 96%|█████████▌| 49/51 [00:13<00:00, 3.49it/s]\n 98%|█████████▊| 50/51 [00:14<00:00, 3.50it/s]\n100%|██████████| 51/51 [00:14<00:00, 3.51it/s]\n100%|██████████| 51/51 [00:14<00:00, 3.57it/s]",
"metrics": {
"predict_time": 15.706281,
"total_time": 24.946104
},
"output": [
"https://replicate.delivery/mgxm/d3c1458b-c2a7-446d-8799-9bd0bf2d6cbc/out-0.png"
],
"started_at": "2022-09-19T20:41:20.728074Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/lhd5ocvcubgtfbqemc67xqs3ue",
"cancel": "https://api.replicate.com/v1/predictions/lhd5ocvcubgtfbqemc67xqs3ue/cancel"
},
"version": "57d8c937dead2f8437b8c93e586fa8dec20841dfdfc63ff5b4719ee8b867d483"
}Generated in
Using seed: 939
Global seed set to 939
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