defaultAn astronaut riding a rainbow unicorn, cinematic, dramatic
typetext
{
"apply_watermark": true,
"batched_prompt": false,
"condition_scale": 0.45,
"controlnet_image": "https://replicate.delivery/pbxt/JsNziYC0Ha190bMKRDwkR5FpRGDrewOXzGH7mneGnHG4jREV/1f8edf0a-6ae1-4021-8ad2-e866e98d6efd.png",
"guidance_scale": 2,
"height": 1024,
"lora_scale": 0.9,
"lora_weights": "https://pbxt.replicate.delivery/QmdRkthSZmqTEBMgVi17OqpdKkafyLTS6TGmzTF5Qbo9d13IA/trained_model.tar",
"negative_prompt": "",
"num_inference_steps": 6,
"num_outputs": 1,
"prompt": "shot in the style of sksfer, a boy playing with some toys",
"prompt_strength": 0.8,
"scheduler": "LCM",
"width": 1024
}npm install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_OSX**********************************
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 fermatresearch/sdxl-lcm-lora-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"fermatresearch/sdxl-lcm-lora-controlnet:d9db096aec79855d1f42d2bd4fc89f2b1ddf7dcd00118a0e21b8f1d5c03be099",
{
input: {
apply_watermark: true,
batched_prompt: false,
condition_scale: 0.45,
controlnet_image: "https://replicate.delivery/pbxt/JsNziYC0Ha190bMKRDwkR5FpRGDrewOXzGH7mneGnHG4jREV/1f8edf0a-6ae1-4021-8ad2-e866e98d6efd.png",
guidance_scale: 2,
height: 1024,
lora_scale: 0.9,
lora_weights: "https://pbxt.replicate.delivery/QmdRkthSZmqTEBMgVi17OqpdKkafyLTS6TGmzTF5Qbo9d13IA/trained_model.tar",
negative_prompt: "",
num_inference_steps: 6,
num_outputs: 1,
prompt: "shot in the style of sksfer, a boy playing with some toys",
prompt_strength: 0.8,
scheduler: "LCM",
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_OSX**********************************
This is your API token. Keep it to yourself.
import replicate
Run fermatresearch/sdxl-lcm-lora-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"fermatresearch/sdxl-lcm-lora-controlnet:d9db096aec79855d1f42d2bd4fc89f2b1ddf7dcd00118a0e21b8f1d5c03be099",
input={
"apply_watermark": True,
"batched_prompt": False,
"condition_scale": 0.45,
"controlnet_image": "https://replicate.delivery/pbxt/JsNziYC0Ha190bMKRDwkR5FpRGDrewOXzGH7mneGnHG4jREV/1f8edf0a-6ae1-4021-8ad2-e866e98d6efd.png",
"guidance_scale": 2,
"height": 1024,
"lora_scale": 0.9,
"lora_weights": "https://pbxt.replicate.delivery/QmdRkthSZmqTEBMgVi17OqpdKkafyLTS6TGmzTF5Qbo9d13IA/trained_model.tar",
"negative_prompt": "",
"num_inference_steps": 6,
"num_outputs": 1,
"prompt": "shot in the style of sksfer, a boy playing with some toys",
"prompt_strength": 0.8,
"scheduler": "LCM",
"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_OSX**********************************
This is your API token. Keep it to yourself.
Run fermatresearch/sdxl-lcm-lora-controlnet 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": "fermatresearch/sdxl-lcm-lora-controlnet:d9db096aec79855d1f42d2bd4fc89f2b1ddf7dcd00118a0e21b8f1d5c03be099",
"input": {
"apply_watermark": true,
"batched_prompt": false,
"condition_scale": 0.45,
"controlnet_image": "https://replicate.delivery/pbxt/JsNziYC0Ha190bMKRDwkR5FpRGDrewOXzGH7mneGnHG4jREV/1f8edf0a-6ae1-4021-8ad2-e866e98d6efd.png",
"guidance_scale": 2,
"height": 1024,
"lora_scale": 0.9,
"lora_weights": "https://pbxt.replicate.delivery/QmdRkthSZmqTEBMgVi17OqpdKkafyLTS6TGmzTF5Qbo9d13IA/trained_model.tar",
"negative_prompt": "",
"num_inference_steps": 6,
"num_outputs": 1,
"prompt": "shot in the style of sksfer, a boy playing with some toys",
"prompt_strength": 0.8,
"scheduler": "LCM",
"width": 1024
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
{
"id": "szk7rylbfq6aosmfuvkfczlogm",
"model": "fermatresearch/sdxl-lcm-lora-controlnet",
"version": "d9db096aec79855d1f42d2bd4fc89f2b1ddf7dcd00118a0e21b8f1d5c03be099",
"input": {
"apply_watermark": true,
"batched_prompt": false,
"condition_scale": 0.45,
"controlnet_image": "https://replicate.delivery/pbxt/JsNziYC0Ha190bMKRDwkR5FpRGDrewOXzGH7mneGnHG4jREV/1f8edf0a-6ae1-4021-8ad2-e866e98d6efd.png",
"guidance_scale": 2,
"height": 1024,
"lora_scale": 0.9,
"lora_weights": "https://pbxt.replicate.delivery/QmdRkthSZmqTEBMgVi17OqpdKkafyLTS6TGmzTF5Qbo9d13IA/trained_model.tar",
"negative_prompt": "",
"num_inference_steps": 6,
"num_outputs": 1,
"prompt": "shot in the style of sksfer, a boy playing with some toys",
"prompt_strength": 0.8,
"scheduler": "LCM",
"width": 1024
},
"logs": "Using seed: 59453\nskipping loading .. weights already loaded\nPrompt: shot in the style of <s0><s1>, a boy playing with some toys\nThe config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n 0%| | 0/6 [00:00<?, ?it/s]\n 17%|█▋ | 1/6 [00:00<00:01, 4.77it/s]\n 33%|███▎ | 2/6 [00:00<00:00, 4.77it/s]\n 50%|█████ | 3/6 [00:00<00:00, 4.77it/s]\n 67%|██████▋ | 4/6 [00:00<00:00, 4.76it/s]\n 83%|████████▎ | 5/6 [00:01<00:00, 4.76it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.76it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.76it/s]",
"output": [
"https://replicate.delivery/pbxt/URStBauvk2KTHl0Be5UaczWxPPdeX5cDm4fyvQYYQ876dowjA/out-0.png"
],
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2023-11-14T15:26:50.711437Z",
"started_at": "2023-11-14T15:26:50.768442Z",
"completed_at": "2023-11-14T15:26:54.48443Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/szk7rylbfq6aosmfuvkfczlogm/cancel",
"get": "https://api.replicate.com/v1/predictions/szk7rylbfq6aosmfuvkfczlogm"
},
"metrics": {
"predict_time": 3.715988,
"total_time": 3.772993
}
}
