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fofr /sdxl-halo-ring:54731324
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";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run fofr/sdxl-halo-ring using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"fofr/sdxl-halo-ring:547313244f1263d30820606f84b3daa84fa4207a6d7ea3d03a78768a0b24f4d8",
{
input: {
image: "https://replicate.delivery/pbxt/JobaJd8nIXAcOEq8rN8MLP25j4yvFiV2gkafPVD0aMIs6ZYo/out-0-52.png",
width: 1152,
height: 768,
prompt: "An epic landscape photo of a TOK halo ring, low angle, mountains, sunset",
refine: "expert_ensemble_refiner",
scheduler: "K_EULER",
lora_scale: 0.6,
num_outputs: 4,
guidance_scale: 7.5,
apply_watermark: false,
high_noise_frac: 0.9,
negative_prompt: "video game render",
prompt_strength: 0.68,
num_inference_steps: 30
}
}
);
console.log(output);
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 fofr/sdxl-halo-ring using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"fofr/sdxl-halo-ring:547313244f1263d30820606f84b3daa84fa4207a6d7ea3d03a78768a0b24f4d8",
input={
"image": "https://replicate.delivery/pbxt/JobaJd8nIXAcOEq8rN8MLP25j4yvFiV2gkafPVD0aMIs6ZYo/out-0-52.png",
"width": 1152,
"height": 768,
"prompt": "An epic landscape photo of a TOK halo ring, low angle, mountains, sunset",
"refine": "expert_ensemble_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 4,
"guidance_scale": 7.5,
"apply_watermark": False,
"high_noise_frac": 0.9,
"negative_prompt": "video game render",
"prompt_strength": 0.68,
"num_inference_steps": 30
}
)
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 fofr/sdxl-halo-ring 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": "547313244f1263d30820606f84b3daa84fa4207a6d7ea3d03a78768a0b24f4d8",
"input": {
"image": "https://replicate.delivery/pbxt/JobaJd8nIXAcOEq8rN8MLP25j4yvFiV2gkafPVD0aMIs6ZYo/out-0-52.png",
"width": 1152,
"height": 768,
"prompt": "An epic landscape photo of a TOK halo ring, low angle, mountains, sunset",
"refine": "expert_ensemble_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 4,
"guidance_scale": 7.5,
"apply_watermark": false,
"high_noise_frac": 0.9,
"negative_prompt": "video game render",
"prompt_strength": 0.68,
"num_inference_steps": 30
}
}' \
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/fofr/sdxl-halo-ring@sha256:547313244f1263d30820606f84b3daa84fa4207a6d7ea3d03a78768a0b24f4d8 \
-i 'image="https://replicate.delivery/pbxt/JobaJd8nIXAcOEq8rN8MLP25j4yvFiV2gkafPVD0aMIs6ZYo/out-0-52.png"' \
-i 'width=1152' \
-i 'height=768' \
-i 'prompt="An epic landscape photo of a TOK halo ring, low angle, mountains, sunset"' \
-i 'refine="expert_ensemble_refiner"' \
-i 'scheduler="K_EULER"' \
-i 'lora_scale=0.6' \
-i 'num_outputs=4' \
-i 'guidance_scale=7.5' \
-i 'apply_watermark=false' \
-i 'high_noise_frac=0.9' \
-i 'negative_prompt="video game render"' \
-i 'prompt_strength=0.68' \
-i 'num_inference_steps=30'
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/fofr/sdxl-halo-ring@sha256:547313244f1263d30820606f84b3daa84fa4207a6d7ea3d03a78768a0b24f4d8
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "image": "https://replicate.delivery/pbxt/JobaJd8nIXAcOEq8rN8MLP25j4yvFiV2gkafPVD0aMIs6ZYo/out-0-52.png", "width": 1152, "height": 768, "prompt": "An epic landscape photo of a TOK halo ring, low angle, mountains, sunset", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "video game render", "prompt_strength": 0.68, "num_inference_steps": 30 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
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Output
{
"completed_at": "2023-11-03T23:49:07.289354Z",
"created_at": "2023-11-03T23:48:45.008845Z",
"data_removed": false,
"error": null,
"id": "zvgermdbmzxjsv47j3dc4mbkqy",
"input": {
"image": "https://replicate.delivery/pbxt/JobaJd8nIXAcOEq8rN8MLP25j4yvFiV2gkafPVD0aMIs6ZYo/out-0-52.png",
"width": 1152,
"height": 768,
"prompt": "An epic landscape photo of a TOK halo ring, low angle, mountains, sunset",
"refine": "expert_ensemble_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 4,
"guidance_scale": 7.5,
"apply_watermark": false,
"high_noise_frac": 0.9,
"negative_prompt": "video game render",
"prompt_strength": 0.68,
"num_inference_steps": 30
},
"logs": "Using seed: 47633\nEnsuring enough disk space...\nFree disk space: 1499370766336\nDownloading weights: https://replicate.delivery/pbxt/fk1MISGQ7k0RQC52whA6SsEGU4KTfneaSdaWES4fdgUkaNTHB/trained_model.tar\nb'Downloaded 186 MB bytes in 0.661s (281 MB/s)\\nExtracted 186 MB in 0.051s (3.6 GB/s)\\n'\nDownloaded weights in 0.8109667301177979 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: An epic landscape photo of a <s0><s1> halo ring, low angle, mountains, sunset\nimg2img mode\n 0%| | 0/11 [00:00<?, ?it/s]\n 9%|▉ | 1/11 [00:00<00:08, 1.11it/s]\n 18%|█▊ | 2/11 [00:01<00:08, 1.11it/s]\n 27%|██▋ | 3/11 [00:02<00:07, 1.11it/s]\n 36%|███▋ | 4/11 [00:03<00:06, 1.11it/s]\n 45%|████▌ | 5/11 [00:04<00:05, 1.12it/s]\n 55%|█████▍ | 6/11 [00:05<00:04, 1.12it/s]\n 64%|██████▎ | 7/11 [00:06<00:03, 1.12it/s]\n 73%|███████▎ | 8/11 [00:07<00:02, 1.12it/s]\n 82%|████████▏ | 9/11 [00:08<00:01, 1.12it/s]\n 91%|█████████ | 10/11 [00:08<00:00, 1.12it/s]\n100%|██████████| 11/11 [00:09<00:00, 1.12it/s]\n100%|██████████| 11/11 [00:09<00:00, 1.12it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:01, 1.37it/s]\n 67%|██████▋ | 2/3 [00:01<00:00, 1.36it/s]\n100%|██████████| 3/3 [00:02<00:00, 1.36it/s]\n100%|██████████| 3/3 [00:02<00:00, 1.36it/s]",
"metrics": {
"predict_time": 19.910318,
"total_time": 22.280509
},
"output": [
"https://replicate.delivery/pbxt/87ioKavc1M6tL9xOIKZUaffokefiiheWZtdv4YBeUB8C84MdE/out-0.png",
"https://replicate.delivery/pbxt/v1OrY332jQaJKth2yUY6uY2LurX4eGzg67pORiFrTvr4xZ6IA/out-1.png",
"https://replicate.delivery/pbxt/WlzuF687QCLFLl1Ki3Mvf7ekfoklNSTL1n0xMjQVikJkHnpjA/out-2.png",
"https://replicate.delivery/pbxt/u8UF43OaqgqhDZjegsv9VOEO14OyheTv1uXJoJH5CevlHnpjA/out-3.png"
],
"started_at": "2023-11-03T23:48:47.379036Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/zvgermdbmzxjsv47j3dc4mbkqy",
"cancel": "https://api.replicate.com/v1/predictions/zvgermdbmzxjsv47j3dc4mbkqy/cancel"
},
"version": "547313244f1263d30820606f84b3daa84fa4207a6d7ea3d03a78768a0b24f4d8"
}
Using seed: 47633
Ensuring enough disk space...
Free disk space: 1499370766336
Downloading weights: https://replicate.delivery/pbxt/fk1MISGQ7k0RQC52whA6SsEGU4KTfneaSdaWES4fdgUkaNTHB/trained_model.tar
b'Downloaded 186 MB bytes in 0.661s (281 MB/s)\nExtracted 186 MB in 0.051s (3.6 GB/s)\n'
Downloaded weights in 0.8109667301177979 seconds
Loading fine-tuned model
Does not have Unet. assume we are using LoRA
Loading Unet LoRA
Prompt: An epic landscape photo of a <s0><s1> halo ring, low angle, mountains, sunset
img2img mode
0%| | 0/11 [00:00<?, ?it/s]
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