Readme
This model doesn't have a readme.
An SDXL fine-tune based on Tim Burton’s characters
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 grabielairu/burton using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"grabielairu/burton:77477219ca41ceac6edcbbd5becfd99c6f042a8ad7555fd185883bc7944aa082",
{
input: {
width: 1024,
height: 1024,
prompt: "A TOK man eating spaghetti ",
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 grabielairu/burton using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"grabielairu/burton:77477219ca41ceac6edcbbd5becfd99c6f042a8ad7555fd185883bc7944aa082",
input={
"width": 1024,
"height": 1024,
"prompt": "A TOK man eating spaghetti ",
"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 grabielairu/burton 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": "77477219ca41ceac6edcbbd5becfd99c6f042a8ad7555fd185883bc7944aa082",
"input": {
"width": 1024,
"height": 1024,
"prompt": "A TOK man eating spaghetti ",
"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 grabielairu/burton using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/grabielairu/burton@sha256:77477219ca41ceac6edcbbd5becfd99c6f042a8ad7555fd185883bc7944aa082 \
-i 'width=1024' \
-i 'height=1024' \
-i 'prompt="A TOK man eating spaghetti "' \
-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 grabielairu/burton 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/grabielairu/burton@sha256:77477219ca41ceac6edcbbd5becfd99c6f042a8ad7555fd185883bc7944aa082
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "A TOK man eating spaghetti ", "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 $0.020. Alternatively, try out our featured models for free.
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{
"completed_at": "2023-09-09T19:41:53.228964Z",
"created_at": "2023-09-09T19:41:37.587874Z",
"data_removed": false,
"error": null,
"id": "rg7rwe3bs5n36ywimcftxkxreq",
"input": {
"width": 1024,
"height": 1024,
"prompt": "A TOK man eating spaghetti ",
"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,
"prompt_strength": 0.8,
"num_inference_steps": 50
},
"logs": "Using seed: 61295\nPrompt: A <s0><s1> man eating spaghetti\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.70it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.69it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.70it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.70it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.69it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.70it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.70it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.70it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.70it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.70it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.69it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.69it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.69it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.69it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.69it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.69it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.69it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.69it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.69it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.69it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.69it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.69it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.69it/s]\n 50%|█████ | 25/50 [00:06<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 [00:07<00:05, 3.69it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.68it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.68it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.68it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.68it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.68it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.68it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.67it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.67it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.67it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.67it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.67it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.67it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.67it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.67it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.67it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.68it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.68it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.67it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.67it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.67it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.67it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.68it/s]",
"metrics": {
"predict_time": 15.639732,
"total_time": 15.64109
},
"output": [
"https://replicate.delivery/pbxt/xYfAh5mQmEwpYqQGAq90SDBXGA9kDx6FyVKSLCQdboBA5TxIA/out-0.png"
],
"started_at": "2023-09-09T19:41:37.589232Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/rg7rwe3bs5n36ywimcftxkxreq",
"cancel": "https://api.replicate.com/v1/predictions/rg7rwe3bs5n36ywimcftxkxreq/cancel"
},
"version": "77477219ca41ceac6edcbbd5becfd99c6f042a8ad7555fd185883bc7944aa082"
}
Using seed: 61295
Prompt: A <s0><s1> man eating spaghetti
txt2img mode
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This model costs approximately $0.020 to run on Replicate, or 50 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 21 seconds. The predict time for this model varies significantly based on the inputs.
This model doesn't have a readme.
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: 61295
Prompt: A <s0><s1> man eating spaghetti
txt2img mode
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