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Input
Run this model in Node.js with one line of code:
npx create-replicate --model=qr2ai/360
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run qr2ai/360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"qr2ai/360:b91bedc2d614127b658c7fb2e9276749827cdaf4f94f77ef51635ac60cbedfb9",
{
input: {
prompt: "Cosmic-themed digital painting with a swirling galaxy backdrop in purple, black, and white hues, featuring sparkling stars and glowing accents for depth and motion",
output_format: "webp"
}
}
);
// 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.
Install Replicate’s Python client library:
pip install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun qr2ai/360 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"qr2ai/360:b91bedc2d614127b658c7fb2e9276749827cdaf4f94f77ef51635ac60cbedfb9",
input={
"prompt": "Cosmic-themed digital painting with a swirling galaxy backdrop in purple, black, and white hues, featuring sparkling stars and glowing accents for depth and motion",
"output_format": "webp"
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run qr2ai/360 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": "qr2ai/360:b91bedc2d614127b658c7fb2e9276749827cdaf4f94f77ef51635ac60cbedfb9",
"input": {
"prompt": "Cosmic-themed digital painting with a swirling galaxy backdrop in purple, black, and white hues, featuring sparkling stars and glowing accents for depth and motion",
"output_format": "webp"
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
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Output
{
"completed_at": "2024-07-23T21:46:33.725525Z",
"created_at": "2024-07-23T21:40:15.415000Z",
"data_removed": false,
"error": null,
"id": "fxj2bddfpxrge0cgw64ts9qscw",
"input": {
"prompt": "Cosmic-themed digital painting with a swirling galaxy backdrop in purple, black, and white hues, featuring sparkling stars and glowing accents for depth and motion",
"output_format": "webp"
},
"logs": "Checking inputs\n====================================\nChecking weights\n✅ 360RedmondResized.safetensors exists in ComfyUI/models/loras\n✅ sdxl_vae.safetensors exists in ComfyUI/models/vae\n✅ dreamshaperXL_v21TurboDPMSDE.safetensors exists in ComfyUI/models/checkpoints\n====================================\nRandomising seed to 589244072\nRunning workflow\ngot prompt\nExecuting node 4, title: Load Checkpoint, class type: CheckpointLoaderSimple\nmodel_type EPS\nUsing pytorch attention in VAE\nUsing pytorch attention in VAE\nloaded straight to GPU\nRequested to load SDXL\nLoading 1 new model\nExecuting node 10, title: Load LoRA, class type: LoraLoader\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nRequested to load SDXLClipModel\nLoading 1 new model\nExecuting node 7, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 5, title: Empty Latent Image, class type: EmptyLatentImage\nExecuting node 11, title: Jags-XY_tile sampler, class type: xy_Tiling_KSampler\nRequested to load SDXL\nLoading 1 new model\n 0%| | 0/9 [00:00<?, ?it/s]\n 11%|█ | 1/9 [00:04<00:32, 4.06s/it]\n 22%|██▏ | 2/9 [00:07<00:25, 3.68s/it]\n 33%|███▎ | 3/9 [00:10<00:21, 3.56s/it]\n 44%|████▍ | 4/9 [00:14<00:17, 3.51s/it]\n 56%|█████▌ | 5/9 [00:17<00:13, 3.49s/it]\n 67%|██████▋ | 6/9 [00:21<00:10, 3.48s/it]\n 78%|███████▊ | 7/9 [00:24<00:06, 3.49s/it]\n 89%|████████▉ | 8/9 [00:28<00:03, 3.49s/it]\n100%|██████████| 9/9 [00:29<00:00, 2.95s/it]\n100%|██████████| 9/9 [00:29<00:00, 3.33s/it]\nExecuting node 22, title: Load VAE, class type: VAELoader\nUsing pytorch attention in VAE\nUsing pytorch attention in VAE\nRequested to load AutoencoderKL\nLoading 1 new model\nExecuting node 15, title: Jags-CircularVAEDecode, class type: CircularVAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 46.64 seconds\noutputs: {'9': {'images': [{'filename': 'Image_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nImage_00001_.png",
"metrics": {
"predict_time": 48.162423512,
"total_time": 378.310525
},
"output": [
"https://replicate.delivery/czjl/Nb1Nm5gfXlSHIKoQb2zEKeflfPeCLSGimkumNcGTLBHKXrbZC/Image_00001_.webp"
],
"started_at": "2024-07-23T21:45:45.563101Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/fxj2bddfpxrge0cgw64ts9qscw",
"cancel": "https://api.replicate.com/v1/predictions/fxj2bddfpxrge0cgw64ts9qscw/cancel"
},
"version": "b91bedc2d614127b658c7fb2e9276749827cdaf4f94f77ef51635ac60cbedfb9"
}Generated in
Checking inputs
====================================
Checking weights
✅ 360RedmondResized.safetensors exists in ComfyUI/models/loras
✅ sdxl_vae.safetensors exists in ComfyUI/models/vae
✅ dreamshaperXL_v21TurboDPMSDE.safetensors exists in ComfyUI/models/checkpoints
====================================
Randomising seed to 589244072
Running workflow
got prompt
Executing node 4, title: Load Checkpoint, class type: CheckpointLoaderSimple
model_type EPS
Using pytorch attention in VAE
Using pytorch attention in VAE
loaded straight to GPU
Requested to load SDXL
Loading 1 new model
Executing node 10, title: Load LoRA, class type: LoraLoader
Executing node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode
Requested to load SDXLClipModel
Loading 1 new model
Executing node 7, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode
Executing node 5, title: Empty Latent Image, class type: EmptyLatentImage
Executing node 11, title: Jags-XY_tile sampler, class type: xy_Tiling_KSampler
Requested to load SDXL
Loading 1 new model
0%| | 0/9 [00:00<?, ?it/s]
11%|█ | 1/9 [00:04<00:32, 4.06s/it]
22%|██▏ | 2/9 [00:07<00:25, 3.68s/it]
33%|███▎ | 3/9 [00:10<00:21, 3.56s/it]
44%|████▍ | 4/9 [00:14<00:17, 3.51s/it]
56%|█████▌ | 5/9 [00:17<00:13, 3.49s/it]
67%|██████▋ | 6/9 [00:21<00:10, 3.48s/it]
78%|███████▊ | 7/9 [00:24<00:06, 3.49s/it]
89%|████████▉ | 8/9 [00:28<00:03, 3.49s/it]
100%|██████████| 9/9 [00:29<00:00, 2.95s/it]
100%|██████████| 9/9 [00:29<00:00, 3.33s/it]
Executing node 22, title: Load VAE, class type: VAELoader
Using pytorch attention in VAE
Using pytorch attention in VAE
Requested to load AutoencoderKL
Loading 1 new model
Executing node 15, title: Jags-CircularVAEDecode, class type: CircularVAEDecode
Executing node 9, title: Save Image, class type: SaveImage
Prompt executed in 46.64 seconds
outputs: {'9': {'images': [{'filename': 'Image_00001_.png', 'subfolder': '', 'type': 'output'}]}}
====================================
Image_00001_.png