typetext
{
"aspect_ratio": "16:9",
"extra_lora_scale": 1,
"guidance_scale": 3.5,
"lora_scale": 1,
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 1,
"output_format": "png",
"output_quality": 90,
"prompt": "d4dupp3r A square piece of note paper centered on a warm wooden desktop. The note reads:\n\"HELLO WORLD.\n --DAD\"\nA pen and various computer chips sit on the desktop near it.",
"prompt_strength": 0.8
}npm install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_URL**********************************
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 benj-edwards/dads-uppercase-2500-steps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"benj-edwards/dads-uppercase-2500-steps:5a7e2ac6e0ff4c9d30e602c499f57fae1c6b108315cc46c673bb9f051e65c2be",
{
input: {
aspect_ratio: "16:9",
extra_lora_scale: 1,
guidance_scale: 3.5,
lora_scale: 1,
model: "dev",
num_inference_steps: 28,
num_outputs: 1,
output_format: "png",
output_quality: 90,
prompt: "d4dupp3r A square piece of note paper centered on a warm wooden desktop. The note reads:\n\"HELLO WORLD.\n --DAD\"\nA pen and various computer chips sit on the desktop near it.",
prompt_strength: 0.8
}
}
);
// 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_URL**********************************
This is your API token. Keep it to yourself.
import replicate
Run benj-edwards/dads-uppercase-2500-steps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"benj-edwards/dads-uppercase-2500-steps:5a7e2ac6e0ff4c9d30e602c499f57fae1c6b108315cc46c673bb9f051e65c2be",
input={
"aspect_ratio": "16:9",
"extra_lora_scale": 1,
"guidance_scale": 3.5,
"lora_scale": 1,
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 1,
"output_format": "png",
"output_quality": 90,
"prompt": "d4dupp3r A square piece of note paper centered on a warm wooden desktop. The note reads:\n\"HELLO WORLD.\n --DAD\"\nA pen and various computer chips sit on the desktop near it.",
"prompt_strength": 0.8
}
)
# 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_URL**********************************
This is your API token. Keep it to yourself.
Run benj-edwards/dads-uppercase-2500-steps 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": "benj-edwards/dads-uppercase-2500-steps:5a7e2ac6e0ff4c9d30e602c499f57fae1c6b108315cc46c673bb9f051e65c2be",
"input": {
"aspect_ratio": "16:9",
"extra_lora_scale": 1,
"guidance_scale": 3.5,
"lora_scale": 1,
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 1,
"output_format": "png",
"output_quality": 90,
"prompt": "d4dupp3r A square piece of note paper centered on a warm wooden desktop. The note reads:\\n\\"HELLO WORLD.\\n --DAD\\"\\nA pen and various computer chips sit on the desktop near it.",
"prompt_strength": 0.8
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
{
"id": "7qfpaejd3drm00chrgvvgj0dc4",
"model": "benj-edwards/dads-uppercase-2500-steps",
"version": "5a7e2ac6e0ff4c9d30e602c499f57fae1c6b108315cc46c673bb9f051e65c2be",
"input": {
"aspect_ratio": "16:9",
"extra_lora_scale": 1,
"guidance_scale": 3.5,
"lora_scale": 1,
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 1,
"output_format": "png",
"output_quality": 90,
"prompt": "d4dupp3r A square piece of note paper centered on a warm wooden desktop. The note reads:\n\"HELLO WORLD.\n --DAD\"\nA pen and various computer chips sit on the desktop near it.",
"prompt_strength": 0.8
},
"logs": "Using seed: 49973\nPrompt: d4dupp3r A square piece of note paper centered on a warm wooden desktop. The note reads:\n\"HELLO WORLD.\n--DAD\"\nA pen and various computer chips sit on the desktop near it.\n[!] txt2img mode\nUsing dev model\nfree=8811221938176\nDownloading weights\n2024-09-05T22:04:04Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpyag7oqh3/weights url=https://replicate.delivery/yhqm/5zOm1SVudA7NN9PNZFzzYDui2B0s6eVQIwO74kpSHYseS5ZTA/trained_model.tar\n2024-09-05T22:04:05Z | INFO | [ Complete ] dest=/tmp/tmpyag7oqh3/weights size=\"172 MB\" total_elapsed=1.642s url=https://replicate.delivery/yhqm/5zOm1SVudA7NN9PNZFzzYDui2B0s6eVQIwO74kpSHYseS5ZTA/trained_model.tar\nDownloaded weights in 1.67s\nLoaded LoRAs in 10.09s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.54it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.01it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.78it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.68it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.63it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.60it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.58it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.57it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.56it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.55it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.55it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.55it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.55it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.54it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.54it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.54it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.54it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.54it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.54it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.54it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.54it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.54it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.54it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.54it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.54it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.54it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.54it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.54it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.57it/s]",
"output": [
"https://replicate.delivery/yhqm/418i8CZg5SpyBpYhI83XcUccX0UObusdPew4lqZ1xNQz5eZTA/out-0.png"
],
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2024-09-05T22:04:04.251Z",
"started_at": "2024-09-05T22:04:04.29939Z",
"completed_at": "2024-09-05T22:04:23.18282Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/7qfpaejd3drm00chrgvvgj0dc4/cancel",
"get": "https://api.replicate.com/v1/predictions/7qfpaejd3drm00chrgvvgj0dc4",
"web": "https://replicate.com/p/7qfpaejd3drm00chrgvvgj0dc4"
},
"metrics": {
"predict_time": 18.883430136,
"total_time": 18.93182
}
}