You're looking at a specific version of this model. Jump to the model overview.
Input
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run dgtlcorp/tero using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"dgtlcorp/tero:cc45fa51d9570923a2466eecb8544b44bc20a81f40a79f5d14e4de87cff0d897",
{
input: {
model: "dev",
prompt: "A cozy winter coffee shop setting with warm, inviting lighting and rustic wooden interiors. Large windows frame a snowy outdoor scene, with frosted glass and soft natural light streaming in. The Blonde model, with a curvy, hourglass figure enhanced by a BBL, stands confidently near a wooden table. She is wearing beige tero leggings with fleece lining, paired with a long, tailored wool coat that drapes elegantly to mid-thigh. Beneath the coat, she wears a fitted turtleneck top, adding a sophisticated and polished touch to her winter ensemble. Stylish knee-high boots complement the look, ensuring practicality and flair for the colder months.\n\nHer hand lightly rests on the back of the chair, while the other holds a steaming latte, exuding warmth and sophistication. Her face features soft, striking Latina features with long wavy hair cascading over her shoulders. The table beside her is decorated with a croissant on a plate, an open journal, and a branded coffee cup, completing the Starbucks-inspired ambiance. Warm caramel, cream, and forest green tones dominate the scene, with fairy lights and candles subtly glowing in the background. The beige tero leggings, designed for ultimate winter comfort, are the centerpiece, with lighting emphasizing their sleek fit and cozy fleece texture, perfectly balancing style and warm",
go_fast: false,
lora_scale: 1,
megapixels: "1",
num_outputs: 4,
aspect_ratio: "1:1",
output_format: "webp",
guidance_scale: 3,
output_quality: 80,
prompt_strength: 0.8,
extra_lora_scale: 1,
num_inference_steps: 28
}
}
);
// 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=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run dgtlcorp/tero using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"dgtlcorp/tero:cc45fa51d9570923a2466eecb8544b44bc20a81f40a79f5d14e4de87cff0d897",
input={
"model": "dev",
"prompt": "A cozy winter coffee shop setting with warm, inviting lighting and rustic wooden interiors. Large windows frame a snowy outdoor scene, with frosted glass and soft natural light streaming in. The Blonde model, with a curvy, hourglass figure enhanced by a BBL, stands confidently near a wooden table. She is wearing beige tero leggings with fleece lining, paired with a long, tailored wool coat that drapes elegantly to mid-thigh. Beneath the coat, she wears a fitted turtleneck top, adding a sophisticated and polished touch to her winter ensemble. Stylish knee-high boots complement the look, ensuring practicality and flair for the colder months.\n\nHer hand lightly rests on the back of the chair, while the other holds a steaming latte, exuding warmth and sophistication. Her face features soft, striking Latina features with long wavy hair cascading over her shoulders. The table beside her is decorated with a croissant on a plate, an open journal, and a branded coffee cup, completing the Starbucks-inspired ambiance. Warm caramel, cream, and forest green tones dominate the scene, with fairy lights and candles subtly glowing in the background. The beige tero leggings, designed for ultimate winter comfort, are the centerpiece, with lighting emphasizing their sleek fit and cozy fleece texture, perfectly balancing style and warm",
"go_fast": False,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run dgtlcorp/tero 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": "dgtlcorp/tero:cc45fa51d9570923a2466eecb8544b44bc20a81f40a79f5d14e4de87cff0d897",
"input": {
"model": "dev",
"prompt": "A cozy winter coffee shop setting with warm, inviting lighting and rustic wooden interiors. Large windows frame a snowy outdoor scene, with frosted glass and soft natural light streaming in. The Blonde model, with a curvy, hourglass figure enhanced by a BBL, stands confidently near a wooden table. She is wearing beige tero leggings with fleece lining, paired with a long, tailored wool coat that drapes elegantly to mid-thigh. Beneath the coat, she wears a fitted turtleneck top, adding a sophisticated and polished touch to her winter ensemble. Stylish knee-high boots complement the look, ensuring practicality and flair for the colder months.\\n\\nHer hand lightly rests on the back of the chair, while the other holds a steaming latte, exuding warmth and sophistication. Her face features soft, striking Latina features with long wavy hair cascading over her shoulders. The table beside her is decorated with a croissant on a plate, an open journal, and a branded coffee cup, completing the Starbucks-inspired ambiance. Warm caramel, cream, and forest green tones dominate the scene, with fairy lights and candles subtly glowing in the background. The beige tero leggings, designed for ultimate winter comfort, are the centerpiece, with lighting emphasizing their sleek fit and cozy fleece texture, perfectly balancing style and warm",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/dgtlcorp/tero@sha256:cc45fa51d9570923a2466eecb8544b44bc20a81f40a79f5d14e4de87cff0d897 \
-i 'model="dev"' \
-i $'prompt="A cozy winter coffee shop setting with warm, inviting lighting and rustic wooden interiors. Large windows frame a snowy outdoor scene, with frosted glass and soft natural light streaming in. The Blonde model, with a curvy, hourglass figure enhanced by a BBL, stands confidently near a wooden table. She is wearing beige tero leggings with fleece lining, paired with a long, tailored wool coat that drapes elegantly to mid-thigh. Beneath the coat, she wears a fitted turtleneck top, adding a sophisticated and polished touch to her winter ensemble. Stylish knee-high boots complement the look, ensuring practicality and flair for the colder months.\\n\\nHer hand lightly rests on the back of the chair, while the other holds a steaming latte, exuding warmth and sophistication. Her face features soft, striking Latina features with long wavy hair cascading over her shoulders. The table beside her is decorated with a croissant on a plate, an open journal, and a branded coffee cup, completing the Starbucks-inspired ambiance. Warm caramel, cream, and forest green tones dominate the scene, with fairy lights and candles subtly glowing in the background. The beige tero leggings, designed for ultimate winter comfort, are the centerpiece, with lighting emphasizing their sleek fit and cozy fleece texture, perfectly balancing style and warm"' \
-i 'go_fast=false' \
-i 'lora_scale=1' \
-i 'megapixels="1"' \
-i 'num_outputs=4' \
-i 'aspect_ratio="1:1"' \
-i 'output_format="webp"' \
-i 'guidance_scale=3' \
-i 'output_quality=80' \
-i 'prompt_strength=0.8' \
-i 'extra_lora_scale=1' \
-i 'num_inference_steps=28'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/dgtlcorp/tero@sha256:cc45fa51d9570923a2466eecb8544b44bc20a81f40a79f5d14e4de87cff0d897
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "A cozy winter coffee shop setting with warm, inviting lighting and rustic wooden interiors. Large windows frame a snowy outdoor scene, with frosted glass and soft natural light streaming in. The Blonde model, with a curvy, hourglass figure enhanced by a BBL, stands confidently near a wooden table. She is wearing beige tero leggings with fleece lining, paired with a long, tailored wool coat that drapes elegantly to mid-thigh. Beneath the coat, she wears a fitted turtleneck top, adding a sophisticated and polished touch to her winter ensemble. Stylish knee-high boots complement the look, ensuring practicality and flair for the colder months.\\n\\nHer hand lightly rests on the back of the chair, while the other holds a steaming latte, exuding warmth and sophistication. Her face features soft, striking Latina features with long wavy hair cascading over her shoulders. The table beside her is decorated with a croissant on a plate, an open journal, and a branded coffee cup, completing the Starbucks-inspired ambiance. Warm caramel, cream, and forest green tones dominate the scene, with fairy lights and candles subtly glowing in the background. The beige tero leggings, designed for ultimate winter comfort, are the centerpiece, with lighting emphasizing their sleek fit and cozy fleece texture, perfectly balancing style and warm", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
By signing in, you agree to our
terms of service and privacy policy
Output
{
"completed_at": "2025-01-08T21:35:42.782533Z",
"created_at": "2025-01-08T21:35:18.014000Z",
"data_removed": false,
"error": null,
"id": "h5ba46z1zsrm80cm8zbtekbyz0",
"input": {
"model": "dev",
"prompt": "A cozy winter coffee shop setting with warm, inviting lighting and rustic wooden interiors. Large windows frame a snowy outdoor scene, with frosted glass and soft natural light streaming in. The Blonde model, with a curvy, hourglass figure enhanced by a BBL, stands confidently near a wooden table. She is wearing beige tero leggings with fleece lining, paired with a long, tailored wool coat that drapes elegantly to mid-thigh. Beneath the coat, she wears a fitted turtleneck top, adding a sophisticated and polished touch to her winter ensemble. Stylish knee-high boots complement the look, ensuring practicality and flair for the colder months.\n\nHer hand lightly rests on the back of the chair, while the other holds a steaming latte, exuding warmth and sophistication. Her face features soft, striking Latina features with long wavy hair cascading over her shoulders. The table beside her is decorated with a croissant on a plate, an open journal, and a branded coffee cup, completing the Starbucks-inspired ambiance. Warm caramel, cream, and forest green tones dominate the scene, with fairy lights and candles subtly glowing in the background. The beige tero leggings, designed for ultimate winter comfort, are the centerpiece, with lighting emphasizing their sleek fit and cozy fleece texture, perfectly balancing style and warm",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
},
"logs": "2025-01-08 21:35:18.118 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 21:35:18.118 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2773.11it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2662.86it/s]\n2025-01-08 21:35:18.233 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\n2025-01-08 21:35:18.234 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/e3ec5ed2de2cd034\n2025-01-08 21:35:18.349 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-08 21:35:18.349 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 21:35:18.349 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2777.57it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2666.95it/s]\n2025-01-08 21:35:18.463 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s\nUsing seed: 61022\n0it [00:00, ?it/s]\n1it [00:00, 8.34it/s]\n2it [00:00, 5.84it/s]\n3it [00:00, 5.33it/s]\n4it [00:00, 5.12it/s]\n5it [00:00, 5.00it/s]\n6it [00:01, 4.92it/s]\n7it [00:01, 4.87it/s]\n8it [00:01, 4.85it/s]\n9it [00:01, 4.85it/s]\n10it [00:01, 4.83it/s]\n11it [00:02, 4.81it/s]\n12it [00:02, 4.80it/s]\n13it [00:02, 4.80it/s]\n14it [00:02, 4.80it/s]\n15it [00:03, 4.80it/s]\n16it [00:03, 4.80it/s]\n17it [00:03, 4.80it/s]\n18it [00:03, 4.79it/s]\n19it [00:03, 4.80it/s]\n20it [00:04, 4.80it/s]\n21it [00:04, 4.80it/s]\n22it [00:04, 4.79it/s]\n23it [00:04, 4.80it/s]\n24it [00:04, 4.79it/s]\n25it [00:05, 4.79it/s]\n26it [00:05, 4.79it/s]\n27it [00:05, 4.80it/s]\n28it [00:05, 4.80it/s]\n28it [00:05, 4.87it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.83it/s]\n2it [00:00, 4.79it/s]\n3it [00:00, 4.80it/s]\n4it [00:00, 4.79it/s]\n5it [00:01, 4.79it/s]\n6it [00:01, 4.79it/s]\n7it [00:01, 4.78it/s]\n8it [00:01, 4.78it/s]\n9it [00:01, 4.79it/s]\n10it [00:02, 4.78it/s]\n11it [00:02, 4.78it/s]\n12it [00:02, 4.77it/s]\n13it [00:02, 4.77it/s]\n14it [00:02, 4.77it/s]\n15it [00:03, 4.78it/s]\n16it [00:03, 4.78it/s]\n17it [00:03, 4.77it/s]\n18it [00:03, 4.77it/s]\n19it [00:03, 4.77it/s]\n20it [00:04, 4.77it/s]\n21it [00:04, 4.77it/s]\n22it [00:04, 4.77it/s]\n23it [00:04, 4.76it/s]\n24it [00:05, 4.76it/s]\n25it [00:05, 4.76it/s]\n26it [00:05, 4.77it/s]\n27it [00:05, 4.76it/s]\n28it [00:05, 4.76it/s]\n28it [00:05, 4.77it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.82it/s]\n2it [00:00, 4.78it/s]\n3it [00:00, 4.78it/s]\n4it [00:00, 4.78it/s]\n5it [00:01, 4.77it/s]\n6it [00:01, 4.76it/s]\n7it [00:01, 4.76it/s]\n8it [00:01, 4.76it/s]\n9it [00:01, 4.76it/s]\n10it [00:02, 4.76it/s]\n11it [00:02, 4.76it/s]\n12it [00:02, 4.76it/s]\n13it [00:02, 4.77it/s]\n14it [00:02, 4.77it/s]\n15it [00:03, 4.76it/s]\n16it [00:03, 4.76it/s]\n17it [00:03, 4.76it/s]\n18it [00:03, 4.76it/s]\n19it [00:03, 4.76it/s]\n20it [00:04, 4.76it/s]\n21it [00:04, 4.76it/s]\n22it [00:04, 4.76it/s]\n23it [00:04, 4.76it/s]\n24it [00:05, 4.77it/s]\n25it [00:05, 4.77it/s]\n26it [00:05, 4.76it/s]\n27it [00:05, 4.76it/s]\n28it [00:05, 4.76it/s]\n28it [00:05, 4.76it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.79it/s]\n2it [00:00, 4.77it/s]\n3it [00:00, 4.76it/s]\n4it [00:00, 4.76it/s]\n5it [00:01, 4.76it/s]\n6it [00:01, 4.75it/s]\n7it [00:01, 4.75it/s]\n8it [00:01, 4.75it/s]\n9it [00:01, 4.75it/s]\n10it [00:02, 4.76it/s]\n11it [00:02, 4.77it/s]\n12it [00:02, 4.77it/s]\n13it [00:02, 4.76it/s]\n14it [00:02, 4.76it/s]\n15it [00:03, 4.76it/s]\n16it [00:03, 4.77it/s]\n17it [00:03, 4.77it/s]\n18it [00:03, 4.76it/s]\n19it [00:03, 4.76it/s]\n20it [00:04, 4.77it/s]\n21it [00:04, 4.77it/s]\n22it [00:04, 4.77it/s]\n23it [00:04, 4.76it/s]\n24it [00:05, 4.76it/s]\n25it [00:05, 4.77it/s]\n26it [00:05, 4.76it/s]\n27it [00:05, 4.77it/s]\n28it [00:05, 4.76it/s]\n28it [00:05, 4.76it/s]\nTotal safe images: 4 out of 4",
"metrics": {
"predict_time": 24.663316508,
"total_time": 24.768533
},
"output": [
"https://replicate.delivery/xezq/nt2lA7NnvF5XMpwoOeVz004HSsxeyWMzLVQrLRRZ29MuGKDUA/out-0.webp",
"https://replicate.delivery/xezq/yTtONX3CBVIeEa7ZJffFNBtcqDCu30eq1AflbgfizshmrhyAF/out-1.webp",
"https://replicate.delivery/xezq/9JLBlFYeiCwDcK9uBQ0FM3hnPvbTG47qLUUpTPWpC1KXDlBKA/out-2.webp",
"https://replicate.delivery/xezq/RbV56B7o92IkEFlV8BGVwdeBrkwM8nNCjAbIaU7OHYKXDlBKA/out-3.webp"
],
"started_at": "2025-01-08T21:35:18.119216Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-onnk6igbiixpmeqqcy44jfmq67y5kwmvb2ry6u5ztnhwtzabzgia",
"get": "https://api.replicate.com/v1/predictions/h5ba46z1zsrm80cm8zbtekbyz0",
"cancel": "https://api.replicate.com/v1/predictions/h5ba46z1zsrm80cm8zbtekbyz0/cancel"
},
"version": "cc45fa51d9570923a2466eecb8544b44bc20a81f40a79f5d14e4de87cff0d897"
}
2025-01-08 21:35:18.118 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-08 21:35:18.118 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2773.11it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2662.86it/s]
2025-01-08 21:35:18.233 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s
2025-01-08 21:35:18.234 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/e3ec5ed2de2cd034
2025-01-08 21:35:18.349 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2025-01-08 21:35:18.349 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-08 21:35:18.349 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2777.57it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2666.95it/s]
2025-01-08 21:35:18.463 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s
Using seed: 61022
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7it [00:01, 4.76it/s]
8it [00:01, 4.76it/s]
9it [00:01, 4.76it/s]
10it [00:02, 4.76it/s]
11it [00:02, 4.76it/s]
12it [00:02, 4.76it/s]
13it [00:02, 4.77it/s]
14it [00:02, 4.77it/s]
15it [00:03, 4.76it/s]
16it [00:03, 4.76it/s]
17it [00:03, 4.76it/s]
18it [00:03, 4.76it/s]
19it [00:03, 4.76it/s]
20it [00:04, 4.76it/s]
21it [00:04, 4.76it/s]
22it [00:04, 4.76it/s]
23it [00:04, 4.76it/s]
24it [00:05, 4.77it/s]
25it [00:05, 4.77it/s]
26it [00:05, 4.76it/s]
27it [00:05, 4.76it/s]
28it [00:05, 4.76it/s]
28it [00:05, 4.76it/s]
0it [00:00, ?it/s]
1it [00:00, 4.79it/s]
2it [00:00, 4.77it/s]
3it [00:00, 4.76it/s]
4it [00:00, 4.76it/s]
5it [00:01, 4.76it/s]
6it [00:01, 4.75it/s]
7it [00:01, 4.75it/s]
8it [00:01, 4.75it/s]
9it [00:01, 4.75it/s]
10it [00:02, 4.76it/s]
11it [00:02, 4.77it/s]
12it [00:02, 4.77it/s]
13it [00:02, 4.76it/s]
14it [00:02, 4.76it/s]
15it [00:03, 4.76it/s]
16it [00:03, 4.77it/s]
17it [00:03, 4.77it/s]
18it [00:03, 4.76it/s]
19it [00:03, 4.76it/s]
20it [00:04, 4.77it/s]
21it [00:04, 4.77it/s]
22it [00:04, 4.77it/s]
23it [00:04, 4.76it/s]
24it [00:05, 4.76it/s]
25it [00:05, 4.77it/s]
26it [00:05, 4.76it/s]
27it [00:05, 4.77it/s]
28it [00:05, 4.76it/s]
28it [00:05, 4.76it/s]
Total safe images: 4 out of 4