arjunbanker / arbgen
testing dreambooth on self
- Public
- 369 runs
-
T4
Want to make some of these yourself?
Run this model
testing dreambooth on self
{
"width": 512,
"height": 512,
"prompt": "arb portrait in the style of satoshi kon + studio ghibli",
"num_outputs": 1,
"guidance_scale": 7.5,
"num_inference_steps": 50
}npm install replicateimport Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run arjunbanker/arbgen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"arjunbanker/arbgen:0d2fe42839d9a057378e884f9ca16c172ae59ebfc150192d9e85f4c3bfcfa1a6",
{
input: {
width: 512,
height: 512,
prompt: "arb portrait in the style of satoshi kon + studio ghibli",
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.
pip install replicateimport replicateRun arjunbanker/arbgen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"arjunbanker/arbgen:0d2fe42839d9a057378e884f9ca16c172ae59ebfc150192d9e85f4c3bfcfa1a6",
input={
"width": 512,
"height": 512,
"prompt": "arb portrait in the style of satoshi kon + studio ghibli",
"num_outputs": 1,
"guidance_scale": 7.5,
"num_inference_steps": 50
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Run arjunbanker/arbgen 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": "arjunbanker/arbgen:0d2fe42839d9a057378e884f9ca16c172ae59ebfc150192d9e85f4c3bfcfa1a6",
"input": {
"width": 512,
"height": 512,
"prompt": "arb portrait in the style of satoshi kon + studio ghibli",
"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.
{
"completed_at": "2022-12-10T22:29:23.076769Z",
"created_at": "2022-12-10T22:29:08.618557Z",
"data_removed": false,
"error": null,
"id": "z6v6p22afbcddlwewvj4tgo5jy",
"input": {
"width": 512,
"height": 512,
"prompt": "arb portrait in the style of satoshi kon + studio ghibli",
"num_outputs": 1,
"guidance_scale": 7.5,
"num_inference_steps": 50
},
"logs": "Loading pipeline...\nUsing seed: 17495\nGlobal seed set to 17495\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:16, 2.96it/s]\n 4%|▍ | 2/50 [00:00<00:14, 3.36it/s]\n 6%|▌ | 3/50 [00:00<00:13, 3.51it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.60it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.61it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.64it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.66it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.65it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.66it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.66it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.67it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.66it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.66it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.66it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.67it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.66it/s]\n 34%|███▍ | 17/50 [00:04<00:09, 3.66it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.66it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.66it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.65it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.65it/s]\n 44%|████▍ | 22/50 [00:06<00:07, 3.66it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.65it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.65it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.65it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.66it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.65it/s]\n 56%|█████▌ | 28/50 [00:07<00:06, 3.65it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.64it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.64it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.64it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.64it/s]\n 66%|██████▌ | 33/50 [00:09<00:04, 3.64it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.64it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.63it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.63it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.63it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.63it/s]\n 78%|███████▊ | 39/50 [00:10<00:03, 3.61it/s]\n 80%|████████ | 40/50 [00:11<00:02, 3.62it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.62it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.62it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.62it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.62it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.62it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.62it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.60it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.61it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.62it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.61it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.63it/s]",
"metrics": {
"predict_time": 14.413876,
"total_time": 14.458212
},
"output": [
"https://replicate.delivery/pbxt/5TVPPsDiIRKTKJT8oWf2gekhaSpvtYezyEDhuJpG2AAESXRgA/out-0.png"
],
"started_at": "2022-12-10T22:29:08.662893Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/z6v6p22afbcddlwewvj4tgo5jy",
"cancel": "https://api.replicate.com/v1/predictions/z6v6p22afbcddlwewvj4tgo5jy/cancel"
},
"version": "0d2fe42839d9a057378e884f9ca16c172ae59ebfc150192d9e85f4c3bfcfa1a6"
}Loading pipeline...
Using seed: 17495
Global seed set to 17495
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100%|██████████| 50/50 [00:13<00:00, 3.63it/s]Want to make some of these yourself?
Run this modelThis model is cold. You'll get a fast response if the model is warm and already running, and a slower response if the model is cold and starting up.
This model runs on T4. View more.
Loading pipeline...
Using seed: 17495
Global seed set to 17495
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