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fofr /sticker-maker:4acb778e
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=fofr/sticker-maker
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";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run fofr/sticker-maker using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"fofr/sticker-maker:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a",
{
input: {
steps: 17,
width: 1152,
height: 1152,
prompt: "a cute cat",
output_format: "webp",
output_quality: 100,
negative_prompt: "",
number_of_images: 1
}
}
);
// 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 fofr/sticker-maker using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"fofr/sticker-maker:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a",
input={
"steps": 17,
"width": 1152,
"height": 1152,
"prompt": "a cute cat",
"output_format": "webp",
"output_quality": 100,
"negative_prompt": "",
"number_of_images": 1
}
)
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 fofr/sticker-maker 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": "fofr/sticker-maker:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a",
"input": {
"steps": 17,
"width": 1152,
"height": 1152,
"prompt": "a cute cat",
"output_format": "webp",
"output_quality": 100,
"negative_prompt": "",
"number_of_images": 1
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
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Output
{
"completed_at": "2024-11-28T11:14:33.380853Z",
"created_at": "2024-11-28T11:14:28.750000Z",
"data_removed": false,
"error": null,
"id": "emmfw2e51srma0cke9x8a31zxm",
"input": {
"steps": 17,
"width": 1152,
"height": 1152,
"prompt": "a cute cat",
"output_format": "webp",
"output_quality": 100,
"negative_prompt": "",
"number_of_images": 1
},
"logs": "Random seed set to: 4001634075\nChecking inputs\n====================================\nChecking weights\n✅ albedobaseXL_v13.safetensors\n✅ layer_xl_transparent_attn.safetensors\n✅ artificialguybr/StickersRedmond.safetensors\n✅ vae_transparent_decoder.safetensors\n====================================\nRunning workflow\ngot prompt\nRequested to load SDXLClipModel\nLoading 1 new model\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 5, title: Empty Latent Image, class type: EmptyLatentImage\nExecuting node 3, title: KSampler, class type: KSampler\n 0%| | 0/17 [00:00<?, ?it/s]\n 6%|▌ | 1/17 [00:00<00:02, 6.59it/s]\n 12%|█▏ | 2/17 [00:00<00:02, 6.81it/s]\n 18%|█▊ | 3/17 [00:00<00:02, 6.89it/s]\n 24%|██▎ | 4/17 [00:00<00:01, 6.93it/s]\n 29%|██▉ | 5/17 [00:00<00:01, 6.93it/s]\n 35%|███▌ | 6/17 [00:00<00:01, 6.95it/s]\n 41%|████ | 7/17 [00:01<00:01, 6.96it/s]\n 47%|████▋ | 8/17 [00:01<00:01, 6.97it/s]\n 53%|█████▎ | 9/17 [00:01<00:01, 6.97it/s]\n 59%|█████▉ | 10/17 [00:01<00:01, 6.97it/s]\n 65%|██████▍ | 11/17 [00:01<00:00, 6.98it/s]\n 71%|███████ | 12/17 [00:01<00:00, 6.99it/s]\n 76%|███████▋ | 13/17 [00:01<00:00, 6.99it/s]\n 82%|████████▏ | 14/17 [00:02<00:00, 6.99it/s]\n 88%|████████▊ | 15/17 [00:02<00:00, 7.00it/s]\n 94%|█████████▍| 16/17 [00:02<00:00, 7.03it/s]\n100%|██████████| 17/17 [00:02<00:00, 7.04it/s]\n100%|██████████| 17/17 [00:02<00:00, 6.97it/s]\nExecuting node 14, title: VAE Decode, class type: VAEDecode\nExecuting node 20, title: Preview Image, class type: PreviewImage\nExecuting node 36, title: Layer Diffuse Decode (RGBA), class type: LayeredDiffusionDecodeRGBA\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:01, 6.03it/s]\n 38%|███▊ | 3/8 [00:00<00:00, 7.85it/s]\n 50%|█████ | 4/8 [00:00<00:00, 7.69it/s]\n 62%|██████▎ | 5/8 [00:00<00:00, 7.60it/s]\n 75%|███████▌ | 6/8 [00:00<00:00, 7.54it/s]\n 88%|████████▊ | 7/8 [00:00<00:00, 7.50it/s]\n100%|██████████| 8/8 [00:01<00:00, 7.48it/s]\n100%|██████████| 8/8 [00:01<00:00, 7.49it/s]\nExecuting node 48, title: Save Image, class type: SaveImage\nPrompt executed in 4.10 seconds\noutputs: {'20': {'images': [{'filename': 'ComfyUI_temp_kmlpk_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '48': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nComfyUI_00001_.png",
"metrics": {
"predict_time": 4.622765286,
"total_time": 4.630853
},
"output": [
"https://replicate.delivery/xezq/ed6kMmOhNz2YfEaGJwmUeSAmzKDFeCPQP8buewJzffMrMFw6JA/ComfyUI_00001_.webp"
],
"started_at": "2024-11-28T11:14:28.758087Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-or2ov7sc7dnal2sp3p53rrtqxnwc2yehb6v2b6zrxtzy6igu3w4q",
"get": "https://api.replicate.com/v1/predictions/emmfw2e51srma0cke9x8a31zxm",
"cancel": "https://api.replicate.com/v1/predictions/emmfw2e51srma0cke9x8a31zxm/cancel"
},
"version": "4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a"
}Generated in
Random seed set to: 4001634075
Checking inputs
====================================
Checking weights
✅ albedobaseXL_v13.safetensors
✅ layer_xl_transparent_attn.safetensors
✅ artificialguybr/StickersRedmond.safetensors
✅ vae_transparent_decoder.safetensors
====================================
Running workflow
got prompt
Requested to load SDXLClipModel
Loading 1 new model
Executing node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode
Executing node 5, title: Empty Latent Image, class type: EmptyLatentImage
Executing node 3, title: KSampler, class type: KSampler
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100%|██████████| 17/17 [00:02<00:00, 6.97it/s]
Executing node 14, title: VAE Decode, class type: VAEDecode
Executing node 20, title: Preview Image, class type: PreviewImage
Executing node 36, title: Layer Diffuse Decode (RGBA), class type: LayeredDiffusionDecodeRGBA
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100%|██████████| 8/8 [00:01<00:00, 7.49it/s]
Executing node 48, title: Save Image, class type: SaveImage
Prompt executed in 4.10 seconds
outputs: {'20': {'images': [{'filename': 'ComfyUI_temp_kmlpk_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '48': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}
====================================
ComfyUI_00001_.png