defaultAn astronaut riding a rainbow unicorn
typetext
{
"apply_watermark": true,
"guidance_scale": 7.5,
"height": 1024,
"high_noise_frac": 0.65,
"lora_scale": 0.7,
"negative_prompt": "ugly, ugly arms, ugly hands,",
"num_inference_steps": 50,
"num_outputs": 3,
"prompt": "Cute small TOK dog sitting in a movie theater eating popcorn watching a movie ,unreal engine, cozy indoor lighting, artstation, detailed, digital painting,cinematic,character design by mark ryden and pixar and hayao miyazaki, unreal 5, daz, hyperrealistic, octane render",
"prompt_strength": 0.6,
"refine": "no_refiner",
"scheduler": "K_EULER",
"width": 1024
}npm install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_TiH**********************************
This is your API token. Keep it to yourself.
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run iamsml/tani_v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"iamsml/tani_v2:583436503fcabd63c177841ee3ff531f2a99cb3ec6783d27e1c0a8d018d64f16",
{
input: {
apply_watermark: true,
guidance_scale: 7.5,
height: 1024,
high_noise_frac: 0.65,
lora_scale: 0.7,
negative_prompt: "ugly, ugly arms, ugly hands,",
num_inference_steps: 50,
num_outputs: 3,
prompt: "Cute small TOK dog sitting in a movie theater eating popcorn watching a movie ,unreal engine, cozy indoor lighting, artstation, detailed, digital painting,cinematic,character design by mark ryden and pixar and hayao miyazaki, unreal 5, daz, hyperrealistic, octane render",
prompt_strength: 0.6,
refine: "no_refiner",
scheduler: "K_EULER",
width: 1024
}
}
);
// 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 replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_TiH**********************************
This is your API token. Keep it to yourself.
import replicate
Run iamsml/tani_v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"iamsml/tani_v2:583436503fcabd63c177841ee3ff531f2a99cb3ec6783d27e1c0a8d018d64f16",
input={
"apply_watermark": True,
"guidance_scale": 7.5,
"height": 1024,
"high_noise_frac": 0.65,
"lora_scale": 0.7,
"negative_prompt": "ugly, ugly arms, ugly hands,",
"num_inference_steps": 50,
"num_outputs": 3,
"prompt": "Cute small TOK dog sitting in a movie theater eating popcorn watching a movie ,unreal engine, cozy indoor lighting, artstation, detailed, digital painting,cinematic,character design by mark ryden and pixar and hayao miyazaki, unreal 5, daz, hyperrealistic, octane render",
"prompt_strength": 0.6,
"refine": "no_refiner",
"scheduler": "K_EULER",
"width": 1024
}
)
# 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.
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_TiH**********************************
This is your API token. Keep it to yourself.
Run iamsml/tani_v2 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": "iamsml/tani_v2:583436503fcabd63c177841ee3ff531f2a99cb3ec6783d27e1c0a8d018d64f16",
"input": {
"apply_watermark": true,
"guidance_scale": 7.5,
"height": 1024,
"high_noise_frac": 0.65,
"lora_scale": 0.7,
"negative_prompt": "ugly, ugly arms, ugly hands,",
"num_inference_steps": 50,
"num_outputs": 3,
"prompt": "Cute small TOK dog sitting in a movie theater eating popcorn watching a movie ,unreal engine, cozy indoor lighting, artstation, detailed, digital painting,cinematic,character design by mark ryden and pixar and hayao miyazaki, unreal 5, daz, hyperrealistic, octane render",
"prompt_strength": 0.6,
"refine": "no_refiner",
"scheduler": "K_EULER",
"width": 1024
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
{
"id": "3wczm6lbjydpm325q6yean3nlq",
"model": "iamsml/tani_v2",
"version": "583436503fcabd63c177841ee3ff531f2a99cb3ec6783d27e1c0a8d018d64f16",
"input": {
"apply_watermark": true,
"guidance_scale": 7.5,
"height": 1024,
"high_noise_frac": 0.65,
"lora_scale": 0.7,
"negative_prompt": "ugly, ugly arms, ugly hands,",
"num_inference_steps": 50,
"num_outputs": 3,
"prompt": "Cute small TOK dog sitting in a movie theater eating popcorn watching a movie ,unreal engine, cozy indoor lighting, artstation, detailed, digital painting,cinematic,character design by mark ryden and pixar and hayao miyazaki, unreal 5, daz, hyperrealistic, octane render",
"prompt_strength": 0.6,
"refine": "no_refiner",
"scheduler": "K_EULER",
"width": 1024
},
"logs": "Using seed: 17260\nPrompt: Cute small <s0><s1> dog sitting in a movie theater eating popcorn watching a movie ,unreal engine, cozy indoor lighting, artstation, detailed, digital painting,cinematic,character design by mark ryden and pixar and hayao miyazaki, unreal 5, daz, hyperrealistic, octane render\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:36, 1.34it/s]\n 4%|▍ | 2/50 [00:01<00:36, 1.33it/s]\n 6%|▌ | 3/50 [00:02<00:35, 1.33it/s]\n 8%|▊ | 4/50 [00:03<00:34, 1.32it/s]\n 10%|█ | 5/50 [00:03<00:33, 1.32it/s]\n 12%|█▏ | 6/50 [00:04<00:33, 1.32it/s]\n 14%|█▍ | 7/50 [00:05<00:32, 1.32it/s]\n 16%|█▌ | 8/50 [00:06<00:31, 1.32it/s]\n 18%|█▊ | 9/50 [00:06<00:31, 1.32it/s]\n 20%|██ | 10/50 [00:07<00:30, 1.32it/s]\n 22%|██▏ | 11/50 [00:08<00:29, 1.32it/s]\n 24%|██▍ | 12/50 [00:09<00:28, 1.32it/s]\n 26%|██▌ | 13/50 [00:09<00:27, 1.32it/s]\n 28%|██▊ | 14/50 [00:10<00:27, 1.32it/s]\n 30%|███ | 15/50 [00:11<00:26, 1.32it/s]\n 32%|███▏ | 16/50 [00:12<00:25, 1.32it/s]\n 34%|███▍ | 17/50 [00:12<00:24, 1.32it/s]\n 36%|███▌ | 18/50 [00:13<00:24, 1.32it/s]\n 38%|███▊ | 19/50 [00:14<00:23, 1.32it/s]\n 40%|████ | 20/50 [00:15<00:22, 1.32it/s]\n 42%|████▏ | 21/50 [00:15<00:22, 1.31it/s]\n 44%|████▍ | 22/50 [00:16<00:21, 1.32it/s]\n 46%|████▌ | 23/50 [00:17<00:20, 1.32it/s]\n 48%|████▊ | 24/50 [00:18<00:19, 1.32it/s]\n 50%|█████ | 25/50 [00:18<00:18, 1.32it/s]\n 52%|█████▏ | 26/50 [00:19<00:18, 1.32it/s]\n 54%|█████▍ | 27/50 [00:20<00:17, 1.32it/s]\n 56%|█████▌ | 28/50 [00:21<00:16, 1.32it/s]\n 58%|█████▊ | 29/50 [00:21<00:15, 1.32it/s]\n 60%|██████ | 30/50 [00:22<00:15, 1.32it/s]\n 62%|██████▏ | 31/50 [00:23<00:14, 1.32it/s]\n 64%|██████▍ | 32/50 [00:24<00:13, 1.32it/s]\n 66%|██████▌ | 33/50 [00:24<00:12, 1.32it/s]\n 68%|██████▊ | 34/50 [00:25<00:12, 1.32it/s]\n 70%|███████ | 35/50 [00:26<00:11, 1.32it/s]\n 72%|███████▏ | 36/50 [00:27<00:10, 1.32it/s]\n 74%|███████▍ | 37/50 [00:28<00:09, 1.32it/s]\n 76%|███████▌ | 38/50 [00:28<00:09, 1.32it/s]\n 78%|███████▊ | 39/50 [00:29<00:08, 1.32it/s]\n 80%|████████ | 40/50 [00:30<00:07, 1.32it/s]\n 82%|████████▏ | 41/50 [00:31<00:06, 1.32it/s]\n 84%|████████▍ | 42/50 [00:31<00:06, 1.32it/s]\n 86%|████████▌ | 43/50 [00:32<00:05, 1.32it/s]\n 88%|████████▊ | 44/50 [00:33<00:04, 1.32it/s]\n 90%|█████████ | 45/50 [00:34<00:03, 1.32it/s]\n 92%|█████████▏| 46/50 [00:34<00:03, 1.32it/s]\n 94%|█████████▍| 47/50 [00:35<00:02, 1.32it/s]\n 96%|█████████▌| 48/50 [00:36<00:01, 1.32it/s]\n 98%|█████████▊| 49/50 [00:37<00:00, 1.32it/s]\n100%|██████████| 50/50 [00:37<00:00, 1.32it/s]\n100%|██████████| 50/50 [00:37<00:00, 1.32it/s]",
"output": [
"https://replicate.delivery/pbxt/PGLpbeMXMsTWICtfH6NOmywCTbAppJRQZ32Vs3BCozjsrwgRA/out-0.png",
"https://replicate.delivery/pbxt/DFffaMRuxsk7eJ5aZoO3InvMznBAxvPd7WpTsLutH5dZXhBjA/out-1.png",
"https://replicate.delivery/pbxt/DOE3rRwKfHXbC6effvtUajbyGt8LR2EVx0CV5SDxzJ5yuCDGB/out-2.png"
],
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2023-09-04T04:10:36.325495Z",
"started_at": "2023-09-04T04:10:43.137237Z",
"completed_at": "2023-09-04T04:11:25.184373Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/3wczm6lbjydpm325q6yean3nlq/cancel",
"get": "https://api.replicate.com/v1/predictions/3wczm6lbjydpm325q6yean3nlq"
},
"metrics": {
"predict_time": 42.047136,
"total_time": 48.858878
}
}

