Readme
Training data: https://replicate.delivery/pbxt/JSeVhAkY5kSTd7Nnd8pDiZMeMuC2mQ7VlQgmX4u4whYYkMin/data.zip
SDXL fine-tuned on characters and objects from Richard Scarry's Busytown
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run zeke/busytown using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"zeke/busytown:ad6936e4daadb763ec2e24fa0e77dacc37f298ad7bd1523dda816f7f10c63dd1",
{
input: {
width: 1024,
height: 1024,
prompt: "a warthog driving a pickle car in style of TOK",
refine: "no_refiner",
scheduler: "K_EULER",
lora_scale: 0.6,
num_outputs: 1,
guidance_scale: 7.5,
apply_watermark: true,
high_noise_frac: 0.8,
negative_prompt: "",
prompt_strength: 0.8,
num_inference_steps: 50
}
}
);
console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run zeke/busytown using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"zeke/busytown:ad6936e4daadb763ec2e24fa0e77dacc37f298ad7bd1523dda816f7f10c63dd1",
input={
"width": 1024,
"height": 1024,
"prompt": "a warthog driving a pickle car in style of TOK",
"refine": "no_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": True,
"high_noise_frac": 0.8,
"negative_prompt": "",
"prompt_strength": 0.8,
"num_inference_steps": 50
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run zeke/busytown 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": "ad6936e4daadb763ec2e24fa0e77dacc37f298ad7bd1523dda816f7f10c63dd1",
"input": {
"width": 1024,
"height": 1024,
"prompt": "a warthog driving a pickle car in style of TOK",
"refine": "no_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": true,
"high_noise_frac": 0.8,
"negative_prompt": "",
"prompt_strength": 0.8,
"num_inference_steps": 50
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
brew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run zeke/busytown using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/zeke/busytown@sha256:ad6936e4daadb763ec2e24fa0e77dacc37f298ad7bd1523dda816f7f10c63dd1 \
-i 'width=1024' \
-i 'height=1024' \
-i 'prompt="a warthog driving a pickle car in style of TOK"' \
-i 'refine="no_refiner"' \
-i 'scheduler="K_EULER"' \
-i 'lora_scale=0.6' \
-i 'num_outputs=1' \
-i 'guidance_scale=7.5' \
-i 'apply_watermark=true' \
-i 'high_noise_frac=0.8' \
-i 'negative_prompt=""' \
-i 'prompt_strength=0.8' \
-i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run zeke/busytown 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/zeke/busytown@sha256:ad6936e4daadb763ec2e24fa0e77dacc37f298ad7bd1523dda816f7f10c63dd1
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "a warthog driving a pickle car in style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Add a payment method to run this model.
Each run costs approximately $0.023. Alternatively, try out our featured models for free.
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{
"completed_at": "2023-09-03T03:42:18.436233Z",
"created_at": "2023-09-03T03:42:00.160692Z",
"data_removed": false,
"error": null,
"id": "5matfddbdby2bo36baa5l46kgi",
"input": {
"width": 1024,
"height": 1024,
"prompt": "a warthog driving a pickle car in style of TOK",
"refine": "no_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": true,
"high_noise_frac": 0.8,
"negative_prompt": "",
"prompt_strength": 0.8,
"num_inference_steps": 50
},
"logs": "Using seed: 58072\nPrompt: a warthog driving a pickle car in style of <s0><s1>\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:41, 1.17it/s]\n 4%|▍ | 2/50 [00:01<00:24, 1.95it/s]\n 6%|▌ | 3/50 [00:01<00:18, 2.49it/s]\n 8%|▊ | 4/50 [00:01<00:16, 2.85it/s]\n 10%|█ | 5/50 [00:01<00:14, 3.11it/s]\n 12%|█▏ | 6/50 [00:02<00:13, 3.28it/s]\n 14%|█▍ | 7/50 [00:02<00:12, 3.40it/s]\n 16%|█▌ | 8/50 [00:02<00:12, 3.49it/s]\n 18%|█▊ | 9/50 [00:03<00:11, 3.55it/s]\n 20%|██ | 10/50 [00:03<00:11, 3.59it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.61it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.63it/s]\n 26%|██▌ | 13/50 [00:04<00:10, 3.65it/s]\n 28%|██▊ | 14/50 [00:04<00:09, 3.66it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.66it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.66it/s]\n 34%|███▍ | 17/50 [00:05<00:08, 3.67it/s]\n 36%|███▌ | 18/50 [00:05<00:08, 3.68it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.68it/s]\n 40%|████ | 20/50 [00:06<00:08, 3.69it/s]\n 42%|████▏ | 21/50 [00:06<00:07, 3.69it/s]\n 44%|████▍ | 22/50 [00:06<00:07, 3.69it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s]\n 48%|████▊ | 24/50 [00:07<00:07, 3.69it/s]\n 50%|█████ | 25/50 [00:07<00:06, 3.69it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.69it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.69it/s]\n 56%|█████▌ | 28/50 [00:08<00:05, 3.69it/s]\n 58%|█████▊ | 29/50 [00:08<00:05, 3.69it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.69it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.69it/s]\n 64%|██████▍ | 32/50 [00:09<00:04, 3.69it/s]\n 66%|██████▌ | 33/50 [00:09<00:04, 3.69it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.69it/s]\n 70%|███████ | 35/50 [00:10<00:04, 3.69it/s]\n 72%|███████▏ | 36/50 [00:10<00:03, 3.69it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.69it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.69it/s]\n 78%|███████▊ | 39/50 [00:11<00:02, 3.69it/s]\n 80%|████████ | 40/50 [00:11<00:02, 3.69it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.69it/s]\n 86%|████████▌ | 43/50 [00:12<00:01, 3.69it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.69it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.69it/s]\n 92%|█████████▏| 46/50 [00:13<00:01, 3.68it/s]\n 94%|█████████▍| 47/50 [00:13<00:00, 3.69it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.68it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:14<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:14<00:00, 3.53it/s]",
"metrics": {
"predict_time": 16.772765,
"total_time": 18.275541
},
"output": [
"https://pbxt.replicate.delivery/lVXChtDdofxSAqacCiWGo1oGCHGw11WRbaMag7MFeFLZKbgRA/out-0.png"
],
"started_at": "2023-09-03T03:42:01.663468Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/5matfddbdby2bo36baa5l46kgi",
"cancel": "https://api.replicate.com/v1/predictions/5matfddbdby2bo36baa5l46kgi/cancel"
},
"version": "831e10b3bc3c8ec2139ecad01488166220b9bf47d8efde7d0a5d6e31938dd8ee"
}
Using seed: 58072
Prompt: a warthog driving a pickle car in style of <s0><s1>
txt2img mode
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This example was created by a different version, zeke/busytown:831e10b3.
This model costs approximately $0.023 to run on Replicate, or 43 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.
This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 25 seconds.
Training data: https://replicate.delivery/pbxt/JSeVhAkY5kSTd7Nnd8pDiZMeMuC2mQ7VlQgmX4u4whYYkMin/data.zip
This model is warm. You'll get a fast response if the model is warm and already running, and a slower response if the model is cold and starting up.
Choose a file from your machine
Hint: you can also drag files onto the input
Choose a file from your machine
Hint: you can also drag files onto the input
Using seed: 58072
Prompt: a warthog driving a pickle car in style of <s0><s1>
txt2img mode
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