fofr
/
sticker-maker
Make stickers with AI. Generates graphics with transparent backgrounds.
Prediction
fofr/sticker-maker:4acb778eID7dplyjdbhpgqdoxf2owwpv5gomStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- steps
- 20
- width
- 1024
- height
- 1024
- prompt
- a cute cat
- upscale
- true
- upscale_steps
- 10
- negative_prompt
{ "steps": 20, "width": 1024, "height": 1024, "prompt": "a cute cat", "upscale": true, "upscale_steps": 10, "negative_prompt": "" }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport 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: 20, width: 1024, height: 1024, prompt: "a cute cat", negative_prompt: "" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run 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": 20, "width": 1024, "height": 1024, "prompt": "a cute cat", "negative_prompt": "" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport 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": "4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a", "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "a cute cat", "negative_prompt": "" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sticker-maker using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a \ -i 'steps=20' \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="a cute cat"' \ -i 'negative_prompt=""'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sticker-maker using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "a cute cat", "negative_prompt": "" } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2024-02-23T12:45:45.318436Z", "created_at": "2024-02-23T12:44:45.420757Z", "data_removed": false, "error": null, "id": "7dplyjdbhpgqdoxf2owwpv5gom", "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "a cute cat", "upscale": true, "upscale_steps": 10, "negative_prompt": "" }, "logs": "Random seed set to: 2459425481\nChecking inputs\n====================================\nChecking weights\n✅ RMBG-1.4/model.pth\n✅ albedobaseXL_v13.safetensors\n✅ dreamshaper_8.safetensors\n✅ 4x-AnimeSharp.pth\n✅ artificialguybr/StickersRedmond.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 2, title: Efficient Loader, class type: Efficient Loader\nRequested to load SDXLClipModel\nLoading 1 new model\n----------------------------------------\n\u001b[36mEfficient Loader Models Cache:\u001b[0m\nCkpt:\n[1] albedobaseXL_v13\nLora:\n[1] base_ckpt: albedobaseXL_v13\nlora(mod,clip): StickersRedmond(1,1)\nExecuting node 4, title: KSampler (Efficient), class type: KSampler (Efficient)\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:03, 4.84it/s]\n 10%|█ | 2/20 [00:00<00:03, 4.65it/s]\n 15%|█▌ | 3/20 [00:00<00:03, 4.59it/s]\n 20%|██ | 4/20 [00:00<00:03, 4.57it/s]\n 25%|██▌ | 5/20 [00:01<00:03, 4.58it/s]\n 30%|███ | 6/20 [00:01<00:03, 4.55it/s]\n 35%|███▌ | 7/20 [00:01<00:02, 4.56it/s]\n 40%|████ | 8/20 [00:01<00:02, 4.55it/s]\n 45%|████▌ | 9/20 [00:01<00:02, 4.54it/s]\n 50%|█████ | 10/20 [00:02<00:02, 4.54it/s]\n 55%|█████▌ | 11/20 [00:02<00:01, 4.55it/s]\n 60%|██████ | 12/20 [00:02<00:01, 4.57it/s]\n 65%|██████▌ | 13/20 [00:02<00:01, 4.59it/s]\n 70%|███████ | 14/20 [00:03<00:01, 4.60it/s]\n 75%|███████▌ | 15/20 [00:03<00:01, 4.60it/s]\n 80%|████████ | 16/20 [00:03<00:00, 4.53it/s]\n 85%|████████▌ | 17/20 [00:03<00:00, 4.55it/s]\n 90%|█████████ | 18/20 [00:03<00:00, 4.59it/s]\n 95%|█████████▌| 19/20 [00:04<00:00, 4.74it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.87it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.63it/s]\nExecuting node 11, title: Ultimate SD Upscale, class type: UltimateSDUpscale\nCanva size: 2048x2048\nImage size: 1024x1024\nScale factor: 2\nUpscaling iteration 1 with scale factor 2\nTile size: 512x512\nTiles amount: 16\nGrid: 4x4\nRedraw enabled: True\nSeams fix mode: NONE\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.45it/s]\n 60%|██████ | 6/10 [00:00<00:00, 22.86it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.35it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.61it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.46it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.05it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.42it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.70it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.39it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.12it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.47it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.70it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 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| 9/10 [00:00<00:00, 22.61it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.85it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.29it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.14it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.54it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.79it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.48it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.11it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.62it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.82it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.50it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.26it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.61it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.88it/s]\nExecuting node 16, title: Save Image, class type: SaveImage\nExecuting node 17, title: 🧹BRIA RMBG, class type: BRIA_RMBG_Zho\nExecuting node 18, title: Save Image, class type: SaveImage\nPrompt executed in 22.11 seconds\noutputs: {'4': {'images': [{'filename': 'ComfyUI_temp_qdrly_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '16': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}, '18': {'images': [{'filename': 'ComfyUI_00002_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png\nComfyUI_00002_.png", "metrics": { "predict_time": 24.456625, "total_time": 59.897679 }, "output": [ "https://replicate.delivery/pbxt/WZU3KPmCsg4QFFmzdgCefhyirgoyzbzXBA0ADbediYtvrIzkA/ComfyUI_00001_.png", "https://replicate.delivery/pbxt/uMEMjvQNPewQdSebtYhizgWOS3Qdj9o4Fs92g5QZiYt4VkZSA/ComfyUI_00002_.png" ], "started_at": "2024-02-23T12:45:20.861811Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7dplyjdbhpgqdoxf2owwpv5gom", "cancel": "https://api.replicate.com/v1/predictions/7dplyjdbhpgqdoxf2owwpv5gom/cancel" }, "version": "fbfe71bb555526d022edb3e87b5375ee4bd7500ac0467d0bca1942813f8d5b78" }
Generated inRandom seed set to: 2459425481 Checking inputs ==================================== Checking weights ✅ RMBG-1.4/model.pth ✅ albedobaseXL_v13.safetensors ✅ dreamshaper_8.safetensors ✅ 4x-AnimeSharp.pth ✅ artificialguybr/StickersRedmond.safetensors ==================================== Running workflow got prompt Executing node 2, title: Efficient Loader, class type: Efficient Loader Requested to load SDXLClipModel Loading 1 new model ---------------------------------------- Efficient Loader Models Cache: Ckpt: [1] albedobaseXL_v13 Lora: [1] base_ckpt: albedobaseXL_v13 lora(mod,clip): StickersRedmond(1,1) Executing node 4, title: KSampler (Efficient), class type: KSampler (Efficient) 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:03, 4.84it/s] 10%|█ | 2/20 [00:00<00:03, 4.65it/s] 15%|█▌ | 3/20 [00:00<00:03, 4.59it/s] 20%|██ | 4/20 [00:00<00:03, 4.57it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.58it/s] 30%|███ | 6/20 [00:01<00:03, 4.55it/s] 35%|███▌ | 7/20 [00:01<00:02, 4.56it/s] 40%|████ | 8/20 [00:01<00:02, 4.55it/s] 45%|████▌ | 9/20 [00:01<00:02, 4.54it/s] 50%|█████ | 10/20 [00:02<00:02, 4.54it/s] 55%|█████▌ | 11/20 [00:02<00:01, 4.55it/s] 60%|██████ | 12/20 [00:02<00:01, 4.57it/s] 65%|██████▌ | 13/20 [00:02<00:01, 4.59it/s] 70%|███████ | 14/20 [00:03<00:01, 4.60it/s] 75%|███████▌ | 15/20 [00:03<00:01, 4.60it/s] 80%|████████ | 16/20 [00:03<00:00, 4.53it/s] 85%|████████▌ | 17/20 [00:03<00:00, 4.55it/s] 90%|█████████ | 18/20 [00:03<00:00, 4.59it/s] 95%|█████████▌| 19/20 [00:04<00:00, 4.74it/s] 100%|██████████| 20/20 [00:04<00:00, 4.87it/s] 100%|██████████| 20/20 [00:04<00:00, 4.63it/s] Executing node 11, title: Ultimate SD Upscale, class type: UltimateSDUpscale Canva size: 2048x2048 Image size: 1024x1024 Scale factor: 2 Upscaling iteration 1 with scale factor 2 Tile size: 512x512 Tiles amount: 16 Grid: 4x4 Redraw enabled: True Seams fix mode: NONE 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.45it/s] 60%|██████ | 6/10 [00:00<00:00, 22.86it/s] 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25.53it/s] 60%|██████ | 6/10 [00:00<00:00, 23.08it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.45it/s] 100%|██████████| 10/10 [00:00<00:00, 22.77it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.64it/s] 60%|██████ | 6/10 [00:00<00:00, 23.20it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.60it/s] 100%|██████████| 10/10 [00:00<00:00, 22.86it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.37it/s] 60%|██████ | 6/10 [00:00<00:00, 23.27it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.61it/s] 100%|██████████| 10/10 [00:00<00:00, 22.85it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.29it/s] 60%|██████ | 6/10 [00:00<00:00, 23.14it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.54it/s] 100%|██████████| 10/10 [00:00<00:00, 22.79it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.48it/s] 60%|██████ | 6/10 [00:00<00:00, 23.11it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.62it/s] 100%|██████████| 10/10 [00:00<00:00, 22.82it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.50it/s] 60%|██████ | 6/10 [00:00<00:00, 23.26it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.61it/s] 100%|██████████| 10/10 [00:00<00:00, 22.88it/s] Executing node 16, title: Save Image, class type: SaveImage Executing node 17, title: 🧹BRIA RMBG, class type: BRIA_RMBG_Zho Executing node 18, title: Save Image, class type: SaveImage Prompt executed in 22.11 seconds outputs: {'4': {'images': [{'filename': 'ComfyUI_temp_qdrly_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '16': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}, '18': {'images': [{'filename': 'ComfyUI_00002_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== Contents of /tmp/outputs: ComfyUI_00001_.png ComfyUI_00002_.png
Prediction
fofr/sticker-maker:4acb778eIDctsbjd3bvhc5bk4l4uu6vhw43eStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- steps
- 20
- width
- 1024
- height
- 1024
- prompt
- an angry penguin
- upscale
- true
- upscale_steps
- 10
- negative_prompt
{ "steps": 20, "width": 1024, "height": 1024, "prompt": "an angry penguin", "upscale": true, "upscale_steps": 10, "negative_prompt": "" }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport 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: 20, width: 1024, height: 1024, prompt: "an angry penguin", negative_prompt: "" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run 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": 20, "width": 1024, "height": 1024, "prompt": "an angry penguin", "negative_prompt": "" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport 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": "4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a", "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "an angry penguin", "negative_prompt": "" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sticker-maker using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a \ -i 'steps=20' \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="an angry penguin"' \ -i 'negative_prompt=""'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sticker-maker using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "an angry penguin", "negative_prompt": "" } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2024-02-23T12:48:44.223144Z", "created_at": "2024-02-23T12:48:19.093562Z", "data_removed": false, "error": null, "id": "ctsbjd3bvhc5bk4l4uu6vhw43e", "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "an angry penguin", "upscale": true, "upscale_steps": 10, "negative_prompt": "" }, "logs": "Random seed set to: 3216572800\nChecking inputs\n====================================\nChecking weights\n✅ artificialguybr/StickersRedmond.safetensors\n✅ albedobaseXL_v13.safetensors\n✅ 4x-AnimeSharp.pth\n✅ RMBG-1.4/model.pth\n✅ dreamshaper_8.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 2, title: Efficient Loader, class type: Efficient Loader\nRequested to load SDXLClipModel\nLoading 1 new model\n----------------------------------------\n\u001b[36mEfficient Loader Models Cache:\u001b[0m\nCkpt:\n[1] albedobaseXL_v13\nLora:\n[1] base_ckpt: albedobaseXL_v13\nlora(mod,clip): StickersRedmond(1,1)\nExecuting node 4, title: KSampler (Efficient), class type: KSampler (Efficient)\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:03, 4.93it/s]\n 10%|█ | 2/20 [00:00<00:03, 4.71it/s]\n 15%|█▌ | 3/20 [00:00<00:03, 4.64it/s]\n 20%|██ | 4/20 [00:00<00:03, 4.03it/s]\n 25%|██▌ | 5/20 [00:01<00:03, 4.17it/s]\n 30%|███ | 6/20 [00:01<00:03, 4.09it/s]\n 35%|███▌ | 7/20 [00:01<00:03, 4.25it/s]\n 40%|████ | 8/20 [00:01<00:02, 4.32it/s]\n 45%|████▌ | 9/20 [00:02<00:02, 4.35it/s]\n 50%|█████ | 10/20 [00:02<00:02, 4.40it/s]\n 55%|█████▌ | 11/20 [00:02<00:02, 4.36it/s]\n 60%|██████ | 12/20 [00:02<00:01, 4.43it/s]\n 65%|██████▌ | 13/20 [00:02<00:01, 4.47it/s]\n 70%|███████ | 14/20 [00:03<00:01, 4.51it/s]\n 75%|███████▌ | 15/20 [00:03<00:01, 4.50it/s]\n 80%|████████ | 16/20 [00:03<00:00, 4.54it/s]\n 85%|████████▌ | 17/20 [00:03<00:00, 4.57it/s]\n 90%|█████████ | 18/20 [00:04<00:00, 4.58it/s]\n 95%|█████████▌| 19/20 [00:04<00:00, 4.75it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.93it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.50it/s]\nExecuting node 11, title: Ultimate SD Upscale, class type: UltimateSDUpscale\nCanva size: 2048x2048\nImage size: 1024x1024\nScale factor: 2\nUpscaling iteration 1 with scale factor 2\nTile size: 512x512\nTiles amount: 16\nGrid: 4x4\nRedraw enabled: True\nSeams fix mode: NONE\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.10it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.34it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.62it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.81it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.40it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.26it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.64it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.90it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.44it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.29it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.70it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.94it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 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| 9/10 [00:00<00:00, 22.62it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.88it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.35it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.26it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.65it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.87it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.50it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.30it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.72it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.97it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.68it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.40it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.77it/s]\n100%|██████████| 10/10 [00:00<00:00, 23.01it/s]\nExecuting node 16, title: Save Image, class type: SaveImage\nExecuting node 17, title: 🧹BRIA RMBG, class type: BRIA_RMBG_Zho\nExecuting node 18, title: Save Image, class type: SaveImage\nPrompt executed in 22.51 seconds\noutputs: {'4': {'images': [{'filename': 'ComfyUI_temp_lsamm_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '16': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}, '18': {'images': [{'filename': 'ComfyUI_00002_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png\nComfyUI_00002_.png", "metrics": { "predict_time": 25.087023, "total_time": 25.129582 }, "output": [ "https://replicate.delivery/pbxt/kiEPt46ZkdISIpPApxKP2JV34VME8peM5yAU2E0YM2JVMyMJA/ComfyUI_00001_.png", "https://replicate.delivery/pbxt/uzunUrfAUlzLUSHSBqEROF3zZyp8R61enPRZk8MnzMPrYkZSA/ComfyUI_00002_.png" ], "started_at": "2024-02-23T12:48:19.136121Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ctsbjd3bvhc5bk4l4uu6vhw43e", "cancel": "https://api.replicate.com/v1/predictions/ctsbjd3bvhc5bk4l4uu6vhw43e/cancel" }, "version": "3b2fc090362c3c344456a32b62e4277e4c03e82f0e24c549fa8d01042218f87c" }
Generated inRandom seed set to: 3216572800 Checking inputs ==================================== Checking weights ✅ artificialguybr/StickersRedmond.safetensors ✅ albedobaseXL_v13.safetensors ✅ 4x-AnimeSharp.pth ✅ RMBG-1.4/model.pth ✅ dreamshaper_8.safetensors ==================================== Running workflow got prompt Executing node 2, title: Efficient Loader, class type: Efficient Loader Requested to load SDXLClipModel Loading 1 new model ---------------------------------------- Efficient Loader Models Cache: Ckpt: [1] albedobaseXL_v13 Lora: [1] base_ckpt: albedobaseXL_v13 lora(mod,clip): StickersRedmond(1,1) Executing node 4, title: KSampler (Efficient), class type: KSampler (Efficient) 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:03, 4.93it/s] 10%|█ | 2/20 [00:00<00:03, 4.71it/s] 15%|█▌ | 3/20 [00:00<00:03, 4.64it/s] 20%|██ | 4/20 [00:00<00:03, 4.03it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.17it/s] 30%|███ | 6/20 [00:01<00:03, 4.09it/s] 35%|███▌ | 7/20 [00:01<00:03, 4.25it/s] 40%|████ | 8/20 [00:01<00:02, 4.32it/s] 45%|████▌ | 9/20 [00:02<00:02, 4.35it/s] 50%|█████ | 10/20 [00:02<00:02, 4.40it/s] 55%|█████▌ | 11/20 [00:02<00:02, 4.36it/s] 60%|██████ | 12/20 [00:02<00:01, 4.43it/s] 65%|██████▌ | 13/20 [00:02<00:01, 4.47it/s] 70%|███████ | 14/20 [00:03<00:01, 4.51it/s] 75%|███████▌ | 15/20 [00:03<00:01, 4.50it/s] 80%|████████ | 16/20 [00:03<00:00, 4.54it/s] 85%|████████▌ | 17/20 [00:03<00:00, 4.57it/s] 90%|█████████ | 18/20 [00:04<00:00, 4.58it/s] 95%|█████████▌| 19/20 [00:04<00:00, 4.75it/s] 100%|██████████| 20/20 [00:04<00:00, 4.93it/s] 100%|██████████| 20/20 [00:04<00:00, 4.50it/s] Executing node 11, title: Ultimate SD Upscale, class type: UltimateSDUpscale Canva size: 2048x2048 Image size: 1024x1024 Scale factor: 2 Upscaling iteration 1 with scale factor 2 Tile size: 512x512 Tiles amount: 16 Grid: 4x4 Redraw enabled: True Seams fix mode: NONE 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.10it/s] 60%|██████ | 6/10 [00:00<00:00, 23.34it/s] 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25.45it/s] 60%|██████ | 6/10 [00:00<00:00, 23.28it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.65it/s] 100%|██████████| 10/10 [00:00<00:00, 22.91it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.54it/s] 60%|██████ | 6/10 [00:00<00:00, 23.21it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.51it/s] 100%|██████████| 10/10 [00:00<00:00, 22.81it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.55it/s] 60%|██████ | 6/10 [00:00<00:00, 23.19it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.62it/s] 100%|██████████| 10/10 [00:00<00:00, 22.88it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.35it/s] 60%|██████ | 6/10 [00:00<00:00, 23.26it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.65it/s] 100%|██████████| 10/10 [00:00<00:00, 22.87it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.50it/s] 60%|██████ | 6/10 [00:00<00:00, 23.30it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.72it/s] 100%|██████████| 10/10 [00:00<00:00, 22.97it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.68it/s] 60%|██████ | 6/10 [00:00<00:00, 23.40it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.77it/s] 100%|██████████| 10/10 [00:00<00:00, 23.01it/s] Executing node 16, title: Save Image, class type: SaveImage Executing node 17, title: 🧹BRIA RMBG, class type: BRIA_RMBG_Zho Executing node 18, title: Save Image, class type: SaveImage Prompt executed in 22.51 seconds outputs: {'4': {'images': [{'filename': 'ComfyUI_temp_lsamm_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '16': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}, '18': {'images': [{'filename': 'ComfyUI_00002_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== Contents of /tmp/outputs: ComfyUI_00001_.png ComfyUI_00002_.png
Prediction
fofr/sticker-maker:4acb778eIDcmghfm3bsu3hw6op7enka26cieStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- steps
- 20
- width
- 1024
- height
- 1024
- prompt
- pikachu, simple, clean
- upscale
- true
- upscale_steps
- 10
{ "steps": 20, "width": 1024, "height": 1024, "prompt": "pikachu, simple, clean", "upscale": true, "upscale_steps": 10 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport 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: 20, width: 1024, height: 1024, prompt: "pikachu, simple, clean" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run 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": 20, "width": 1024, "height": 1024, "prompt": "pikachu, simple, clean" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport 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": "4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a", "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "pikachu, simple, clean" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sticker-maker using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a \ -i 'steps=20' \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="pikachu, simple, clean"'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sticker-maker using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "pikachu, simple, clean" } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2024-02-23T12:53:11.618948Z", "created_at": "2024-02-23T12:52:48.049803Z", "data_removed": false, "error": null, "id": "cmghfm3bsu3hw6op7enka26cie", "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "pikachu, simple, clean", "upscale": true, "upscale_steps": 10 }, "logs": "Random seed set to: 3457628994\nChecking inputs\n====================================\nChecking weights\n✅ artificialguybr/StickersRedmond.safetensors\n✅ albedobaseXL_v13.safetensors\n✅ 4x-AnimeSharp.pth\n✅ RMBG-1.4/model.pth\n✅ dreamshaper_8.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 4, title: KSampler (Efficient), class type: KSampler (Efficient)\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:03, 4.92it/s]\n 10%|█ | 2/20 [00:00<00:03, 4.80it/s]\n 15%|█▌ | 3/20 [00:00<00:03, 4.75it/s]\n 20%|██ | 4/20 [00:00<00:03, 4.75it/s]\n 25%|██▌ | 5/20 [00:01<00:03, 4.77it/s]\n 30%|███ | 6/20 [00:01<00:02, 4.74it/s]\n 35%|███▌ | 7/20 [00:01<00:02, 4.72it/s]\n 40%|████ | 8/20 [00:01<00:02, 4.67it/s]\n 45%|████▌ | 9/20 [00:01<00:02, 4.63it/s]\n 50%|█████ | 10/20 [00:02<00:02, 4.61it/s]\n 55%|█████▌ | 11/20 [00:02<00:02, 4.49it/s]\n 60%|██████ | 12/20 [00:02<00:01, 4.54it/s]\n 65%|██████▌ | 13/20 [00:02<00:01, 4.56it/s]\n 70%|███████ | 14/20 [00:03<00:01, 4.59it/s]\n 75%|███████▌ | 15/20 [00:03<00:01, 4.58it/s]\n 80%|████████ | 16/20 [00:03<00:00, 4.60it/s]\n 85%|████████▌ | 17/20 [00:03<00:00, 4.61it/s]\n 90%|█████████ | 18/20 [00:03<00:00, 4.64it/s]\n 95%|█████████▌| 19/20 [00:04<00:00, 4.75it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.92it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.69it/s]\nExecuting node 11, title: Ultimate SD Upscale, class type: UltimateSDUpscale\nCanva size: 2048x2048\nImage size: 1024x1024\nScale factor: 2\nUpscaling iteration 1 with scale factor 2\nTile size: 512x512\nTiles amount: 16\nGrid: 4x4\nRedraw enabled: True\nSeams fix mode: NONE\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 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90%|█████████ | 9/10 [00:00<00:00, 22.73it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.96it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.47it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.36it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.72it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.94it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.44it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.27it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.75it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.95it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.47it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.30it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.62it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.91it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.17it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.28it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.72it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.86it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.13it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.21it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.63it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.85it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.27it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.07it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.63it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.82it/s]\nExecuting node 16, title: Save Image, class type: SaveImage\nExecuting node 17, title: 🧹BRIA RMBG, class type: BRIA_RMBG_Zho\nExecuting node 18, title: Save Image, class type: SaveImage\nPrompt executed in 21.24 seconds\noutputs: {'4': {'images': [{'filename': 'ComfyUI_temp_duimf_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '16': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}, '18': {'images': [{'filename': 'ComfyUI_00002_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png\nComfyUI_00002_.png", "metrics": { "predict_time": 23.504271, "total_time": 23.569145 }, "output": [ "https://replicate.delivery/pbxt/o6Y0CfYIud3uXKVXm41rTK4jV87Hpe5UFX3wHN5yppC1ckZSA/ComfyUI_00001_.png", "https://replicate.delivery/pbxt/IwuKQonhCnYkLx6t4tLvezFFLTfQG54ADBYpyVcWUll3ckZSA/ComfyUI_00002_.png" ], "started_at": "2024-02-23T12:52:48.114677Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/cmghfm3bsu3hw6op7enka26cie", "cancel": "https://api.replicate.com/v1/predictions/cmghfm3bsu3hw6op7enka26cie/cancel" }, "version": "3b2fc090362c3c344456a32b62e4277e4c03e82f0e24c549fa8d01042218f87c" }
Generated inRandom seed set to: 3457628994 Checking inputs ==================================== Checking weights ✅ artificialguybr/StickersRedmond.safetensors ✅ albedobaseXL_v13.safetensors ✅ 4x-AnimeSharp.pth ✅ RMBG-1.4/model.pth ✅ dreamshaper_8.safetensors ==================================== Running workflow got prompt Executing node 4, title: KSampler (Efficient), class type: KSampler (Efficient) 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:03, 4.92it/s] 10%|█ | 2/20 [00:00<00:03, 4.80it/s] 15%|█▌ | 3/20 [00:00<00:03, 4.75it/s] 20%|██ | 4/20 [00:00<00:03, 4.75it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.77it/s] 30%|███ | 6/20 [00:01<00:02, 4.74it/s] 35%|███▌ | 7/20 [00:01<00:02, 4.72it/s] 40%|████ | 8/20 [00:01<00:02, 4.67it/s] 45%|████▌ | 9/20 [00:01<00:02, 4.63it/s] 50%|█████ | 10/20 [00:02<00:02, 4.61it/s] 55%|█████▌ | 11/20 [00:02<00:02, 4.49it/s] 60%|██████ | 12/20 [00:02<00:01, 4.54it/s] 65%|██████▌ | 13/20 [00:02<00:01, 4.56it/s] 70%|███████ | 14/20 [00:03<00:01, 4.59it/s] 75%|███████▌ | 15/20 [00:03<00:01, 4.58it/s] 80%|████████ | 16/20 [00:03<00:00, 4.60it/s] 85%|████████▌ | 17/20 [00:03<00:00, 4.61it/s] 90%|█████████ | 18/20 [00:03<00:00, 4.64it/s] 95%|█████████▌| 19/20 [00:04<00:00, 4.75it/s] 100%|██████████| 20/20 [00:04<00:00, 4.92it/s] 100%|██████████| 20/20 [00:04<00:00, 4.69it/s] Executing node 11, title: Ultimate SD Upscale, class type: UltimateSDUpscale Canva size: 2048x2048 Image size: 1024x1024 Scale factor: 2 Upscaling iteration 1 with scale factor 2 Tile size: 512x512 Tiles amount: 16 Grid: 4x4 Redraw enabled: True Seams fix mode: NONE 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.13it/s] 60%|██████ | 6/10 [00:00<00:00, 23.14it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.58it/s] 100%|██████████| 10/10 [00:00<00:00, 22.78it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 24.95it/s] 60%|██████ | 6/10 [00:00<00:00, 22.68it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.30it/s] 100%|██████████| 10/10 [00:00<00:00, 22.55it/s] 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22.75it/s] 100%|██████████| 10/10 [00:00<00:00, 22.95it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.47it/s] 60%|██████ | 6/10 [00:00<00:00, 23.30it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.62it/s] 100%|██████████| 10/10 [00:00<00:00, 22.91it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.17it/s] 60%|██████ | 6/10 [00:00<00:00, 23.28it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.72it/s] 100%|██████████| 10/10 [00:00<00:00, 22.86it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.13it/s] 60%|██████ | 6/10 [00:00<00:00, 23.21it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.63it/s] 100%|██████████| 10/10 [00:00<00:00, 22.85it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.27it/s] 60%|██████ | 6/10 [00:00<00:00, 23.07it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.63it/s] 100%|██████████| 10/10 [00:00<00:00, 22.82it/s] Executing node 16, title: Save Image, class type: SaveImage Executing node 17, title: 🧹BRIA RMBG, class type: BRIA_RMBG_Zho Executing node 18, title: Save Image, class type: SaveImage Prompt executed in 21.24 seconds outputs: {'4': {'images': [{'filename': 'ComfyUI_temp_duimf_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '16': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}, '18': {'images': [{'filename': 'ComfyUI_00002_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== Contents of /tmp/outputs: ComfyUI_00001_.png ComfyUI_00002_.png
Prediction
fofr/sticker-maker:4acb778eIDfcg7lrtbpygvie5ypd4ikamowiStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- steps
- 20
- width
- 1024
- height
- 1024
- prompt
- cute dragon
- upscale
- true
- upscale_steps
- 10
- negative_prompt
- bubbles
{ "steps": 20, "width": 1024, "height": 1024, "prompt": "cute dragon", "upscale": true, "upscale_steps": 10, "negative_prompt": "bubbles" }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport 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: 20, width: 1024, height: 1024, prompt: "cute dragon", negative_prompt: "bubbles" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run 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": 20, "width": 1024, "height": 1024, "prompt": "cute dragon", "negative_prompt": "bubbles" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport 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": "4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a", "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "cute dragon", "negative_prompt": "bubbles" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sticker-maker using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a \ -i 'steps=20' \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="cute dragon"' \ -i 'negative_prompt="bubbles"'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sticker-maker using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "cute dragon", "negative_prompt": "bubbles" } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2024-02-23T12:56:09.682235Z", "created_at": "2024-02-23T12:55:44.773131Z", "data_removed": false, "error": null, "id": "fcg7lrtbpygvie5ypd4ikamowi", "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "cute dragon", "upscale": true, "upscale_steps": 10, "negative_prompt": "bubbles" }, "logs": "Random seed set to: 964472788\nChecking inputs\n====================================\nChecking weights\n✅ artificialguybr/StickersRedmond.safetensors\n✅ albedobaseXL_v13.safetensors\n✅ 4x-AnimeSharp.pth\n✅ RMBG-1.4/model.pth\n✅ dreamshaper_8.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 2, title: Efficient Loader, class type: Efficient Loader\nRequested to load SDXLClipModel\nLoading 1 new model\n----------------------------------------\n\u001b[36mEfficient Loader Models Cache:\u001b[0m\nCkpt:\n[1] albedobaseXL_v13\nLora:\n[1] base_ckpt: albedobaseXL_v13\nlora(mod,clip): StickersRedmond(1,1)\nExecuting node 4, title: KSampler (Efficient), class type: KSampler (Efficient)\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:04, 4.71it/s]\n 10%|█ | 2/20 [00:00<00:03, 4.61it/s]\n 15%|█▌ | 3/20 [00:00<00:03, 4.60it/s]\n 20%|██ | 4/20 [00:00<00:03, 4.59it/s]\n 25%|██▌ | 5/20 [00:01<00:03, 4.61it/s]\n 30%|███ | 6/20 [00:01<00:03, 4.59it/s]\n 35%|███▌ | 7/20 [00:01<00:02, 4.61it/s]\n 40%|████ | 8/20 [00:01<00:02, 4.59it/s]\n 45%|████▌ | 9/20 [00:01<00:02, 4.59it/s]\n 50%|█████ | 10/20 [00:02<00:02, 4.57it/s]\n 55%|█████▌ | 11/20 [00:02<00:01, 4.59it/s]\n 60%|██████ | 12/20 [00:02<00:01, 4.62it/s]\n 65%|██████▌ | 13/20 [00:02<00:01, 4.64it/s]\n 70%|███████ | 14/20 [00:03<00:01, 4.66it/s]\n 75%|███████▌ | 15/20 [00:03<00:01, 4.65it/s]\n 80%|████████ | 16/20 [00:03<00:00, 4.65it/s]\n 85%|████████▌ | 17/20 [00:03<00:00, 4.65it/s]\n 90%|█████████ | 18/20 [00:03<00:00, 4.67it/s]\n 95%|█████████▌| 19/20 [00:04<00:00, 4.73it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.90it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.67it/s]\nExecuting node 11, title: Ultimate SD Upscale, class type: UltimateSDUpscale\nCanva size: 2048x2048\nImage size: 1024x1024\nScale factor: 2\nUpscaling iteration 1 with scale factor 2\nTile size: 512x512\nTiles amount: 16\nGrid: 4x4\nRedraw enabled: True\nSeams fix mode: NONE\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.38it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.33it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.67it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.91it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.45it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.31it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.56it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.85it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 24.92it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.37it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.55it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.89it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 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90%|█████████ | 9/10 [00:00<00:00, 22.63it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.82it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 24.77it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.14it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.58it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.79it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 24.99it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.13it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.57it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.68it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 24.70it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.39it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.64it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.80it/s]\nExecuting node 16, title: Save Image, class type: SaveImage\nExecuting node 17, title: 🧹BRIA RMBG, class type: BRIA_RMBG_Zho\nExecuting node 18, title: Save Image, class type: SaveImage\nPrompt executed in 22.43 seconds\noutputs: {'4': {'images': [{'filename': 'ComfyUI_temp_osxck_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '16': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}, '18': {'images': [{'filename': 'ComfyUI_00002_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png\nComfyUI_00002_.png", "metrics": { "predict_time": 24.86462, "total_time": 24.909104 }, "output": [ "https://replicate.delivery/pbxt/hauYlnaW2yYdCVoJAXi0vVS1ITdZ0u58pj8eEoMWlp9zPyMJA/ComfyUI_00001_.png", "https://replicate.delivery/pbxt/PDxNQhYhWJ7NBdJQuBqggaq88rDeeWVo1rf7L4unwLESfRmJB/ComfyUI_00002_.png" ], "started_at": "2024-02-23T12:55:44.817615Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/fcg7lrtbpygvie5ypd4ikamowi", "cancel": "https://api.replicate.com/v1/predictions/fcg7lrtbpygvie5ypd4ikamowi/cancel" }, "version": "3b2fc090362c3c344456a32b62e4277e4c03e82f0e24c549fa8d01042218f87c" }
Generated inRandom seed set to: 964472788 Checking inputs ==================================== Checking weights ✅ artificialguybr/StickersRedmond.safetensors ✅ albedobaseXL_v13.safetensors ✅ 4x-AnimeSharp.pth ✅ RMBG-1.4/model.pth ✅ dreamshaper_8.safetensors ==================================== Running workflow got prompt Executing node 2, title: Efficient Loader, class type: Efficient Loader Requested to load SDXLClipModel Loading 1 new model ---------------------------------------- Efficient Loader Models Cache: Ckpt: [1] albedobaseXL_v13 Lora: [1] base_ckpt: albedobaseXL_v13 lora(mod,clip): StickersRedmond(1,1) Executing node 4, title: KSampler (Efficient), class type: KSampler (Efficient) 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:04, 4.71it/s] 10%|█ | 2/20 [00:00<00:03, 4.61it/s] 15%|█▌ | 3/20 [00:00<00:03, 4.60it/s] 20%|██ | 4/20 [00:00<00:03, 4.59it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.61it/s] 30%|███ | 6/20 [00:01<00:03, 4.59it/s] 35%|███▌ | 7/20 [00:01<00:02, 4.61it/s] 40%|████ | 8/20 [00:01<00:02, 4.59it/s] 45%|████▌ | 9/20 [00:01<00:02, 4.59it/s] 50%|█████ | 10/20 [00:02<00:02, 4.57it/s] 55%|█████▌ | 11/20 [00:02<00:01, 4.59it/s] 60%|██████ | 12/20 [00:02<00:01, 4.62it/s] 65%|██████▌ | 13/20 [00:02<00:01, 4.64it/s] 70%|███████ | 14/20 [00:03<00:01, 4.66it/s] 75%|███████▌ | 15/20 [00:03<00:01, 4.65it/s] 80%|████████ | 16/20 [00:03<00:00, 4.65it/s] 85%|████████▌ | 17/20 [00:03<00:00, 4.65it/s] 90%|█████████ | 18/20 [00:03<00:00, 4.67it/s] 95%|█████████▌| 19/20 [00:04<00:00, 4.73it/s] 100%|██████████| 20/20 [00:04<00:00, 4.90it/s] 100%|██████████| 20/20 [00:04<00:00, 4.67it/s] Executing node 11, title: Ultimate SD Upscale, class type: UltimateSDUpscale Canva size: 2048x2048 Image size: 1024x1024 Scale factor: 2 Upscaling iteration 1 with scale factor 2 Tile size: 512x512 Tiles amount: 16 Grid: 4x4 Redraw enabled: True Seams fix mode: NONE 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.38it/s] 60%|██████ | 6/10 [00:00<00:00, 23.33it/s] 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25.14it/s] 60%|██████ | 6/10 [00:00<00:00, 23.10it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.59it/s] 100%|██████████| 10/10 [00:00<00:00, 22.81it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.00it/s] 60%|██████ | 6/10 [00:00<00:00, 23.04it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.59it/s] 100%|██████████| 10/10 [00:00<00:00, 22.77it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 24.99it/s] 60%|██████ | 6/10 [00:00<00:00, 23.07it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.63it/s] 100%|██████████| 10/10 [00:00<00:00, 22.82it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 24.77it/s] 60%|██████ | 6/10 [00:00<00:00, 23.14it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.58it/s] 100%|██████████| 10/10 [00:00<00:00, 22.79it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 24.99it/s] 60%|██████ | 6/10 [00:00<00:00, 23.13it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.57it/s] 100%|██████████| 10/10 [00:00<00:00, 22.68it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 24.70it/s] 60%|██████ | 6/10 [00:00<00:00, 23.39it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.64it/s] 100%|██████████| 10/10 [00:00<00:00, 22.80it/s] Executing node 16, title: Save Image, class type: SaveImage Executing node 17, title: 🧹BRIA RMBG, class type: BRIA_RMBG_Zho Executing node 18, title: Save Image, class type: SaveImage Prompt executed in 22.43 seconds outputs: {'4': {'images': [{'filename': 'ComfyUI_temp_osxck_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '16': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}, '18': {'images': [{'filename': 'ComfyUI_00002_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== Contents of /tmp/outputs: ComfyUI_00001_.png ComfyUI_00002_.png
Prediction
fofr/sticker-maker:4acb778eIDjftgzhtbfw7iphp3velqk4vvz4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- steps
- 20
- width
- 1024
- height
- 1024
- prompt
- cyberpunk
- upscale
- true
- upscale_steps
- 10
- negative_prompt
- bubbles
{ "steps": 20, "width": 1024, "height": 1024, "prompt": "cyberpunk", "upscale": true, "upscale_steps": 10, "negative_prompt": "bubbles" }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport 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: 20, width: 1024, height: 1024, prompt: "cyberpunk", negative_prompt: "bubbles" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run 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": 20, "width": 1024, "height": 1024, "prompt": "cyberpunk", "negative_prompt": "bubbles" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport 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": "4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a", "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "cyberpunk", "negative_prompt": "bubbles" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sticker-maker using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a \ -i 'steps=20' \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="cyberpunk"' \ -i 'negative_prompt="bubbles"'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sticker-maker using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "cyberpunk", "negative_prompt": "bubbles" } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2024-02-23T12:57:37.392413Z", "created_at": "2024-02-23T12:57:12.714123Z", "data_removed": false, "error": null, "id": "jftgzhtbfw7iphp3velqk4vvz4", "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "cyberpunk", "upscale": true, "upscale_steps": 10, "negative_prompt": "bubbles" }, "logs": "Random seed set to: 2178218815\nChecking inputs\n====================================\nChecking weights\n✅ artificialguybr/StickersRedmond.safetensors\n✅ albedobaseXL_v13.safetensors\n✅ 4x-AnimeSharp.pth\n✅ RMBG-1.4/model.pth\n✅ dreamshaper_8.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 2, title: Efficient Loader, class type: Efficient Loader\nRequested to load SDXLClipModel\nLoading 1 new model\n----------------------------------------\n\u001b[36mEfficient Loader Models Cache:\u001b[0m\nCkpt:\n[1] albedobaseXL_v13\nLora:\n[1] base_ckpt: albedobaseXL_v13\nlora(mod,clip): StickersRedmond(1,1)\nExecuting node 4, title: KSampler (Efficient), class type: KSampler (Efficient)\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:03, 4.89it/s]\n 10%|█ | 2/20 [00:00<00:03, 4.68it/s]\n 15%|█▌ | 3/20 [00:00<00:03, 4.59it/s]\n 20%|██ | 4/20 [00:00<00:03, 4.59it/s]\n 25%|██▌ | 5/20 [00:01<00:03, 4.63it/s]\n 30%|███ | 6/20 [00:01<00:03, 4.62it/s]\n 35%|███▌ | 7/20 [00:01<00:02, 4.64it/s]\n 40%|████ | 8/20 [00:01<00:02, 4.63it/s]\n 45%|████▌ | 9/20 [00:01<00:02, 4.63it/s]\n 50%|█████ | 10/20 [00:02<00:02, 4.61it/s]\n 55%|█████▌ | 11/20 [00:02<00:01, 4.63it/s]\n 60%|██████ | 12/20 [00:02<00:01, 4.65it/s]\n 65%|██████▌ | 13/20 [00:02<00:01, 4.66it/s]\n 70%|███████ | 14/20 [00:03<00:01, 4.66it/s]\n 75%|███████▌ | 15/20 [00:03<00:01, 4.66it/s]\n 80%|████████ | 16/20 [00:03<00:00, 4.66it/s]\n 85%|████████▌ | 17/20 [00:03<00:00, 4.68it/s]\n 90%|█████████ | 18/20 [00:03<00:00, 4.69it/s]\n 95%|█████████▌| 19/20 [00:04<00:00, 4.84it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.99it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.71it/s]\nExecuting node 11, title: Ultimate SD Upscale, class type: UltimateSDUpscale\nCanva size: 2048x2048\nImage size: 1024x1024\nScale factor: 2\nUpscaling iteration 1 with scale factor 2\nTile size: 512x512\nTiles amount: 16\nGrid: 4x4\nRedraw enabled: True\nSeams fix mode: NONE\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.49it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.20it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.63it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.88it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.44it/s]\n 60%|██████ | 6/10 [00:00<00:00, 22.69it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.64it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.89it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 24.87it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.44it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.79it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.99it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 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| 9/10 [00:00<00:00, 22.72it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.94it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.24it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.19it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.67it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.89it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.35it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.16it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.69it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.91it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.50it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.27it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.64it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.95it/s]\nExecuting node 16, title: Save Image, class type: SaveImage\nExecuting node 17, title: 🧹BRIA RMBG, class type: BRIA_RMBG_Zho\nExecuting node 18, title: Save Image, class type: SaveImage\nPrompt executed in 22.25 seconds\noutputs: {'4': {'images': [{'filename': 'ComfyUI_temp_vbltq_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '16': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}, '18': {'images': [{'filename': 'ComfyUI_00002_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png\nComfyUI_00002_.png", "metrics": { "predict_time": 24.64185, "total_time": 24.67829 }, "output": [ "https://replicate.delivery/pbxt/p8mAenwuAQXKeUe8RweDx0gtIE3CyAIEgUJfxK4cxGafPIZmE/ComfyUI_00001_.png", "https://replicate.delivery/pbxt/NX0pxsueaLxCZKUf3sh9kM5PDPJBHSqoyyELv6DRuHqAhkZSA/ComfyUI_00002_.png" ], "started_at": "2024-02-23T12:57:12.750563Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/jftgzhtbfw7iphp3velqk4vvz4", "cancel": "https://api.replicate.com/v1/predictions/jftgzhtbfw7iphp3velqk4vvz4/cancel" }, "version": "3b2fc090362c3c344456a32b62e4277e4c03e82f0e24c549fa8d01042218f87c" }
Generated inRandom seed set to: 2178218815 Checking inputs ==================================== Checking weights ✅ artificialguybr/StickersRedmond.safetensors ✅ albedobaseXL_v13.safetensors ✅ 4x-AnimeSharp.pth ✅ RMBG-1.4/model.pth ✅ dreamshaper_8.safetensors ==================================== Running workflow got prompt Executing node 2, title: Efficient Loader, class type: Efficient Loader Requested to load SDXLClipModel Loading 1 new model ---------------------------------------- Efficient Loader Models Cache: Ckpt: [1] albedobaseXL_v13 Lora: [1] base_ckpt: albedobaseXL_v13 lora(mod,clip): StickersRedmond(1,1) Executing node 4, title: KSampler (Efficient), class type: KSampler (Efficient) 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:03, 4.89it/s] 10%|█ | 2/20 [00:00<00:03, 4.68it/s] 15%|█▌ | 3/20 [00:00<00:03, 4.59it/s] 20%|██ | 4/20 [00:00<00:03, 4.59it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.63it/s] 30%|███ | 6/20 [00:01<00:03, 4.62it/s] 35%|███▌ | 7/20 [00:01<00:02, 4.64it/s] 40%|████ | 8/20 [00:01<00:02, 4.63it/s] 45%|████▌ | 9/20 [00:01<00:02, 4.63it/s] 50%|█████ | 10/20 [00:02<00:02, 4.61it/s] 55%|█████▌ | 11/20 [00:02<00:01, 4.63it/s] 60%|██████ | 12/20 [00:02<00:01, 4.65it/s] 65%|██████▌ | 13/20 [00:02<00:01, 4.66it/s] 70%|███████ | 14/20 [00:03<00:01, 4.66it/s] 75%|███████▌ | 15/20 [00:03<00:01, 4.66it/s] 80%|████████ | 16/20 [00:03<00:00, 4.66it/s] 85%|████████▌ | 17/20 [00:03<00:00, 4.68it/s] 90%|█████████ | 18/20 [00:03<00:00, 4.69it/s] 95%|█████████▌| 19/20 [00:04<00:00, 4.84it/s] 100%|██████████| 20/20 [00:04<00:00, 4.99it/s] 100%|██████████| 20/20 [00:04<00:00, 4.71it/s] Executing node 11, title: Ultimate SD Upscale, class type: UltimateSDUpscale Canva size: 2048x2048 Image size: 1024x1024 Scale factor: 2 Upscaling iteration 1 with scale factor 2 Tile size: 512x512 Tiles amount: 16 Grid: 4x4 Redraw enabled: True Seams fix mode: NONE 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.49it/s] 60%|██████ | 6/10 [00:00<00:00, 23.20it/s] 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25.42it/s] 60%|██████ | 6/10 [00:00<00:00, 23.29it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.71it/s] 100%|██████████| 10/10 [00:00<00:00, 22.95it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.47it/s] 60%|██████ | 6/10 [00:00<00:00, 23.35it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.71it/s] 100%|██████████| 10/10 [00:00<00:00, 22.98it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 24.89it/s] 60%|██████ | 6/10 [00:00<00:00, 23.39it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.72it/s] 100%|██████████| 10/10 [00:00<00:00, 22.94it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.24it/s] 60%|██████ | 6/10 [00:00<00:00, 23.19it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.67it/s] 100%|██████████| 10/10 [00:00<00:00, 22.89it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.35it/s] 60%|██████ | 6/10 [00:00<00:00, 23.16it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.69it/s] 100%|██████████| 10/10 [00:00<00:00, 22.91it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.50it/s] 60%|██████ | 6/10 [00:00<00:00, 23.27it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.64it/s] 100%|██████████| 10/10 [00:00<00:00, 22.95it/s] Executing node 16, title: Save Image, class type: SaveImage Executing node 17, title: 🧹BRIA RMBG, class type: BRIA_RMBG_Zho Executing node 18, title: Save Image, class type: SaveImage Prompt executed in 22.25 seconds outputs: {'4': {'images': [{'filename': 'ComfyUI_temp_vbltq_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '16': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}, '18': {'images': [{'filename': 'ComfyUI_00002_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== Contents of /tmp/outputs: ComfyUI_00001_.png ComfyUI_00002_.png
Prediction
fofr/sticker-maker:4acb778eIDzvykyotb466mqmdudyavoizsv4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- steps
- 20
- width
- 1024
- height
- 1024
- prompt
- a toxic yellow smiley face, X eyes
- upscale
- true
- upscale_steps
- 10
- negative_prompt
{ "steps": 20, "width": 1024, "height": 1024, "prompt": "a toxic yellow smiley face, X eyes", "upscale": true, "upscale_steps": 10, "negative_prompt": "" }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport 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: 20, width: 1024, height: 1024, prompt: "a toxic yellow smiley face, X eyes", negative_prompt: "" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run 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": 20, "width": 1024, "height": 1024, "prompt": "a toxic yellow smiley face, X eyes", "negative_prompt": "" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport 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": "4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a", "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "a toxic yellow smiley face, X eyes", "negative_prompt": "" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sticker-maker using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a \ -i 'steps=20' \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="a toxic yellow smiley face, X eyes"' \ -i 'negative_prompt=""'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sticker-maker using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "a toxic yellow smiley face, X eyes", "negative_prompt": "" } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2024-02-23T13:00:46.550368Z", "created_at": "2024-02-23T13:00:21.642918Z", "data_removed": false, "error": null, "id": "zvykyotb466mqmdudyavoizsv4", "input": { "steps": 20, "width": 1024, "height": 1024, "prompt": "a toxic yellow smiley face, X eyes", "upscale": true, "upscale_steps": 10, "negative_prompt": "" }, "logs": "Random seed set to: 2276563659\nChecking inputs\n====================================\nChecking weights\n✅ artificialguybr/StickersRedmond.safetensors\n✅ 4x-AnimeSharp.pth\n✅ RMBG-1.4/model.pth\n✅ dreamshaper_8.safetensors\n✅ albedobaseXL_v13.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 2, title: Efficient Loader, class type: Efficient Loader\nRequested to load SDXLClipModel\nLoading 1 new model\n----------------------------------------\n\u001b[36mEfficient Loader Models Cache:\u001b[0m\nCkpt:\n[1] albedobaseXL_v13\nLora:\n[1] base_ckpt: albedobaseXL_v13\nlora(mod,clip): StickersRedmond(1,1)\nExecuting node 4, title: KSampler (Efficient), class type: KSampler (Efficient)\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:03, 4.87it/s]\n 10%|█ | 2/20 [00:00<00:03, 4.66it/s]\n 15%|█▌ | 3/20 [00:00<00:03, 4.59it/s]\n 20%|██ | 4/20 [00:00<00:03, 4.03it/s]\n 25%|██▌ | 5/20 [00:01<00:03, 4.22it/s]\n 30%|███ | 6/20 [00:01<00:03, 4.30it/s]\n 35%|███▌ | 7/20 [00:01<00:02, 4.38it/s]\n 40%|████ | 8/20 [00:01<00:02, 4.41it/s]\n 45%|████▌ | 9/20 [00:02<00:02, 4.44it/s]\n 50%|█████ | 10/20 [00:02<00:02, 4.48it/s]\n 55%|█████▌ | 11/20 [00:02<00:01, 4.51it/s]\n 60%|██████ | 12/20 [00:02<00:01, 4.54it/s]\n 65%|██████▌ | 13/20 [00:02<00:01, 4.58it/s]\n 70%|███████ | 14/20 [00:03<00:01, 4.60it/s]\n 75%|███████▌ | 15/20 [00:03<00:01, 4.60it/s]\n 80%|████████ | 16/20 [00:03<00:00, 4.61it/s]\n 85%|████████▌ | 17/20 [00:03<00:00, 4.62it/s]\n 90%|█████████ | 18/20 [00:03<00:00, 4.64it/s]\n 95%|█████████▌| 19/20 [00:04<00:00, 4.79it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.93it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.57it/s]\nExecuting node 11, title: Ultimate SD Upscale, class type: UltimateSDUpscale\nCanva size: 2048x2048\nImage size: 1024x1024\nScale factor: 2\nUpscaling iteration 1 with scale factor 2\nTile size: 512x512\nTiles amount: 16\nGrid: 4x4\nRedraw enabled: True\nSeams fix mode: NONE\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.44it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.22it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.64it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.87it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.21it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.30it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.61it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.87it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.29it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.20it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.57it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.82it/s]\n 0%| | 0/10 [00:00<?, 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| 6/10 [00:00<00:00, 21.03it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 21.37it/s]\n100%|██████████| 10/10 [00:00<00:00, 21.67it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.02it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.05it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.45it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.67it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.27it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.18it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.53it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.76it/s]\n 0%| | 0/10 [00:00<?, ?it/s]\n 30%|███ | 3/10 [00:00<00:00, 25.22it/s]\n 60%|██████ | 6/10 [00:00<00:00, 23.15it/s]\n 90%|█████████ | 9/10 [00:00<00:00, 22.34it/s]\n100%|██████████| 10/10 [00:00<00:00, 22.74it/s]\nExecuting node 16, title: Save Image, class type: SaveImage\nExecuting node 17, title: 🧹BRIA RMBG, class type: BRIA_RMBG_Zho\nExecuting node 18, title: Save Image, class type: SaveImage\nPrompt executed in 22.51 seconds\noutputs: {'4': {'images': [{'filename': 'ComfyUI_temp_ufsjp_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '16': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}, '18': {'images': [{'filename': 'ComfyUI_00002_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png\nComfyUI_00002_.png", "metrics": { "predict_time": 24.865925, "total_time": 24.90745 }, "output": [ "https://replicate.delivery/pbxt/lfMTYdFqXDQaYCMpjqTPMjvRjy50d53lknRzAUGluAaejkZSA/ComfyUI_00001_.png", "https://replicate.delivery/pbxt/Jbn4ks6NwxZZMtx11GiQmfELek5RfezWwcVxxVmAt5t5PSmJB/ComfyUI_00002_.png" ], "started_at": "2024-02-23T13:00:21.684443Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zvykyotb466mqmdudyavoizsv4", "cancel": "https://api.replicate.com/v1/predictions/zvykyotb466mqmdudyavoizsv4/cancel" }, "version": "3d72dfb2c09f9502b62f29026415ab0024fb8a2033a145d971a7eb4dc172177d" }
Generated inRandom seed set to: 2276563659 Checking inputs ==================================== Checking weights ✅ artificialguybr/StickersRedmond.safetensors ✅ 4x-AnimeSharp.pth ✅ RMBG-1.4/model.pth ✅ dreamshaper_8.safetensors ✅ albedobaseXL_v13.safetensors ==================================== Running workflow got prompt Executing node 2, title: Efficient Loader, class type: Efficient Loader Requested to load SDXLClipModel Loading 1 new model ---------------------------------------- Efficient Loader Models Cache: Ckpt: [1] albedobaseXL_v13 Lora: [1] base_ckpt: albedobaseXL_v13 lora(mod,clip): StickersRedmond(1,1) Executing node 4, title: KSampler (Efficient), class type: KSampler (Efficient) 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:03, 4.87it/s] 10%|█ | 2/20 [00:00<00:03, 4.66it/s] 15%|█▌ | 3/20 [00:00<00:03, 4.59it/s] 20%|██ | 4/20 [00:00<00:03, 4.03it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.22it/s] 30%|███ | 6/20 [00:01<00:03, 4.30it/s] 35%|███▌ | 7/20 [00:01<00:02, 4.38it/s] 40%|████ | 8/20 [00:01<00:02, 4.41it/s] 45%|████▌ | 9/20 [00:02<00:02, 4.44it/s] 50%|█████ | 10/20 [00:02<00:02, 4.48it/s] 55%|█████▌ | 11/20 [00:02<00:01, 4.51it/s] 60%|██████ | 12/20 [00:02<00:01, 4.54it/s] 65%|██████▌ | 13/20 [00:02<00:01, 4.58it/s] 70%|███████ | 14/20 [00:03<00:01, 4.60it/s] 75%|███████▌ | 15/20 [00:03<00:01, 4.60it/s] 80%|████████ | 16/20 [00:03<00:00, 4.61it/s] 85%|████████▌ | 17/20 [00:03<00:00, 4.62it/s] 90%|█████████ | 18/20 [00:03<00:00, 4.64it/s] 95%|█████████▌| 19/20 [00:04<00:00, 4.79it/s] 100%|██████████| 20/20 [00:04<00:00, 4.93it/s] 100%|██████████| 20/20 [00:04<00:00, 4.57it/s] Executing node 11, title: Ultimate SD Upscale, class type: UltimateSDUpscale Canva size: 2048x2048 Image size: 1024x1024 Scale factor: 2 Upscaling iteration 1 with scale factor 2 Tile size: 512x512 Tiles amount: 16 Grid: 4x4 Redraw enabled: True Seams fix mode: NONE 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.44it/s] 60%|██████ | 6/10 [00:00<00:00, 23.22it/s] 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25.40it/s] 60%|██████ | 6/10 [00:00<00:00, 23.15it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.53it/s] 100%|██████████| 10/10 [00:00<00:00, 22.78it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.38it/s] 60%|██████ | 6/10 [00:00<00:00, 23.06it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.42it/s] 100%|██████████| 10/10 [00:00<00:00, 22.72it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.29it/s] 60%|██████ | 6/10 [00:00<00:00, 21.03it/s] 90%|█████████ | 9/10 [00:00<00:00, 21.37it/s] 100%|██████████| 10/10 [00:00<00:00, 21.67it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.02it/s] 60%|██████ | 6/10 [00:00<00:00, 23.05it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.45it/s] 100%|██████████| 10/10 [00:00<00:00, 22.67it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.27it/s] 60%|██████ | 6/10 [00:00<00:00, 23.18it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.53it/s] 100%|██████████| 10/10 [00:00<00:00, 22.76it/s] 0%| | 0/10 [00:00<?, ?it/s] 30%|███ | 3/10 [00:00<00:00, 25.22it/s] 60%|██████ | 6/10 [00:00<00:00, 23.15it/s] 90%|█████████ | 9/10 [00:00<00:00, 22.34it/s] 100%|██████████| 10/10 [00:00<00:00, 22.74it/s] Executing node 16, title: Save Image, class type: SaveImage Executing node 17, title: 🧹BRIA RMBG, class type: BRIA_RMBG_Zho Executing node 18, title: Save Image, class type: SaveImage Prompt executed in 22.51 seconds outputs: {'4': {'images': [{'filename': 'ComfyUI_temp_ufsjp_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '16': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}, '18': {'images': [{'filename': 'ComfyUI_00002_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== Contents of /tmp/outputs: ComfyUI_00001_.png ComfyUI_00002_.png
Prediction
fofr/sticker-maker:4acb778eIDb1s5rprwcxrgp0cf1ahvvk8apcStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedby @fofrInput
- steps
- 17
- width
- 1152
- height
- 1152
- prompt
- a cute cat
- output_format
- webp
- output_quality
- 100
- negative_prompt
- number_of_images
- 1
{ "steps": 17, "width": 1152, "height": 1152, "prompt": "a cute cat", "output_format": "webp", "output_quality": 100, "negative_prompt": "", "number_of_images": 1 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport 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 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run 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 theREPLICATE_API_TOKEN
environment variableexport 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": "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/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sticker-maker using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a \ -i 'steps=17' \ -i 'width=1152' \ -i 'height=1152' \ -i 'prompt="a cute cat"' \ -i 'output_format="webp"' \ -i 'output_quality=100' \ -i 'negative_prompt=""' \ -i 'number_of_images=1'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sticker-maker using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "steps": 17, "width": 1152, "height": 1152, "prompt": "a cute cat", "output_format": "webp", "output_quality": 100, "negative_prompt": "", "number_of_images": 1 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2024-04-23T11:07:42.785684Z", "created_at": "2024-04-23T11:06:52.903000Z", "data_removed": false, "error": null, "id": "b1s5rprwcxrgp0cf1ahvvk8apc", "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: 1030325473\nChecking inputs\n====================================\nChecking weights\n✅ vae_transparent_decoder.safetensors\n✅ artificialguybr/StickersRedmond.safetensors\n✅ layer_xl_transparent_attn.safetensors\n✅ albedobaseXL_v13.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 7, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nRequested to load SDXLClipModel\nLoading 1 new model\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<00:04, 3.91it/s]\n 12%|█▏ | 2/17 [00:00<00:03, 3.89it/s]\n 18%|█▊ | 3/17 [00:00<00:03, 3.88it/s]\n 24%|██▎ | 4/17 [00:01<00:03, 3.89it/s]\n 29%|██▉ | 5/17 [00:01<00:03, 3.88it/s]\n 35%|███▌ | 6/17 [00:01<00:02, 3.88it/s]\n 41%|████ | 7/17 [00:01<00:02, 3.88it/s]\n 47%|████▋ | 8/17 [00:02<00:02, 3.88it/s]\n 53%|█████▎ | 9/17 [00:02<00:02, 3.88it/s]\n 59%|█████▉ | 10/17 [00:02<00:01, 3.88it/s]\n 65%|██████▍ | 11/17 [00:02<00:01, 3.89it/s]\n 71%|███████ | 12/17 [00:03<00:01, 3.89it/s]\n 76%|███████▋ | 13/17 [00:03<00:01, 3.89it/s]\n 82%|████████▏ | 14/17 [00:03<00:00, 3.89it/s]\n 88%|████████▊ | 15/17 [00:03<00:00, 3.89it/s]\n 94%|█████████▍| 16/17 [00:04<00:00, 3.90it/s]\n100%|██████████| 17/17 [00:04<00:00, 3.91it/s]\n100%|██████████| 17/17 [00:04<00:00, 3.89it/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 25%|██▌ | 2/8 [00:00<00:00, 7.35it/s]\n 38%|███▊ | 3/8 [00:00<00:00, 5.86it/s]\n 50%|█████ | 4/8 [00:00<00:00, 5.30it/s]\n 62%|██████▎ | 5/8 [00:00<00:00, 5.02it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 4.86it/s]\n 88%|████████▊ | 7/8 [00:01<00:00, 4.76it/s]\n100%|██████████| 8/8 [00:01<00:00, 4.69it/s]\n100%|██████████| 8/8 [00:01<00:00, 5.04it/s]\nExecuting node 48, title: Save Image, class type: SaveImage\nPrompt executed in 6.75 seconds\noutputs: {'20': {'images': [{'filename': 'ComfyUI_temp_mhhsy_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '48': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nComfyUI_00001_.png", "metrics": { "predict_time": 8.638063, "total_time": 49.882684 }, "output": [ "https://replicate.delivery/pbxt/89kikrVNWfxve0Oy3YjWHqpXri9FeejOfDbP1Kdhcq7uPkqVC/ComfyUI_00001_.webp" ], "started_at": "2024-04-23T11:07:34.147621Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/b1s5rprwcxrgp0cf1ahvvk8apc", "cancel": "https://api.replicate.com/v1/predictions/b1s5rprwcxrgp0cf1ahvvk8apc/cancel" }, "version": "4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a" }
Generated inRandom seed set to: 1030325473 Checking inputs ==================================== Checking weights ✅ vae_transparent_decoder.safetensors ✅ artificialguybr/StickersRedmond.safetensors ✅ layer_xl_transparent_attn.safetensors ✅ albedobaseXL_v13.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 7, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode Requested to load SDXLClipModel Loading 1 new model Executing node 5, title: Empty Latent Image, class type: EmptyLatentImage Executing node 3, title: KSampler, class type: KSampler 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:04, 3.91it/s] 12%|█▏ | 2/17 [00:00<00:03, 3.89it/s] 18%|█▊ | 3/17 [00:00<00:03, 3.88it/s] 24%|██▎ | 4/17 [00:01<00:03, 3.89it/s] 29%|██▉ | 5/17 [00:01<00:03, 3.88it/s] 35%|███▌ | 6/17 [00:01<00:02, 3.88it/s] 41%|████ | 7/17 [00:01<00:02, 3.88it/s] 47%|████▋ | 8/17 [00:02<00:02, 3.88it/s] 53%|█████▎ | 9/17 [00:02<00:02, 3.88it/s] 59%|█████▉ | 10/17 [00:02<00:01, 3.88it/s] 65%|██████▍ | 11/17 [00:02<00:01, 3.89it/s] 71%|███████ | 12/17 [00:03<00:01, 3.89it/s] 76%|███████▋ | 13/17 [00:03<00:01, 3.89it/s] 82%|████████▏ | 14/17 [00:03<00:00, 3.89it/s] 88%|████████▊ | 15/17 [00:03<00:00, 3.89it/s] 94%|█████████▍| 16/17 [00:04<00:00, 3.90it/s] 100%|██████████| 17/17 [00:04<00:00, 3.91it/s] 100%|██████████| 17/17 [00:04<00:00, 3.89it/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 0%| | 0/8 [00:00<?, ?it/s] 25%|██▌ | 2/8 [00:00<00:00, 7.35it/s] 38%|███▊ | 3/8 [00:00<00:00, 5.86it/s] 50%|█████ | 4/8 [00:00<00:00, 5.30it/s] 62%|██████▎ | 5/8 [00:00<00:00, 5.02it/s] 75%|███████▌ | 6/8 [00:01<00:00, 4.86it/s] 88%|████████▊ | 7/8 [00:01<00:00, 4.76it/s] 100%|██████████| 8/8 [00:01<00:00, 4.69it/s] 100%|██████████| 8/8 [00:01<00:00, 5.04it/s] Executing node 48, title: Save Image, class type: SaveImage Prompt executed in 6.75 seconds outputs: {'20': {'images': [{'filename': 'ComfyUI_temp_mhhsy_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '48': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== ComfyUI_00001_.png
Prediction
fofr/sticker-maker:4acb778eIDemmfw2e51srma0cke9x8a31zxmStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- steps
- 17
- width
- 1152
- height
- 1152
- prompt
- a cute cat
- output_format
- webp
- output_quality
- 100
- negative_prompt
- number_of_images
- 1
{ "steps": 17, "width": 1152, "height": 1152, "prompt": "a cute cat", "output_format": "webp", "output_quality": 100, "negative_prompt": "", "number_of_images": 1 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport 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 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run 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 theREPLICATE_API_TOKEN
environment variableexport 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": "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/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sticker-maker using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a \ -i 'steps=17' \ -i 'width=1152' \ -i 'height=1152' \ -i 'prompt="a cute cat"' \ -i 'output_format="webp"' \ -i 'output_quality=100' \ -i 'negative_prompt=""' \ -i 'number_of_images=1'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sticker-maker using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sticker-maker@sha256:4acb778eb059772225ec213948f0660867b2e03f277448f18cf1800b96a65a1a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "steps": 17, "width": 1152, "height": 1152, "prompt": "a cute cat", "output_format": "webp", "output_quality": 100, "negative_prompt": "", "number_of_images": 1 } }' \ http://localhost:5000/predictions
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 inRandom 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 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 6.59it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.81it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.89it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.93it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.93it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.95it/s] 41%|████ | 7/17 [00:01<00:01, 6.96it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.97it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.97it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.97it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.98it/s] 71%|███████ | 12/17 [00:01<00:00, 6.99it/s] 76%|███████▋ | 13/17 [00:01<00:00, 6.99it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.99it/s] 88%|████████▊ | 15/17 [00:02<00:00, 7.00it/s] 94%|█████████▍| 16/17 [00:02<00:00, 7.03it/s] 100%|██████████| 17/17 [00:02<00:00, 7.04it/s] 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 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:01, 6.03it/s] 38%|███▊ | 3/8 [00:00<00:00, 7.85it/s] 50%|█████ | 4/8 [00:00<00:00, 7.69it/s] 62%|██████▎ | 5/8 [00:00<00:00, 7.60it/s] 75%|███████▌ | 6/8 [00:00<00:00, 7.54it/s] 88%|████████▊ | 7/8 [00:00<00:00, 7.50it/s] 100%|██████████| 8/8 [00:01<00:00, 7.48it/s] 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
Want to make some of these yourself?
Run this model