Readme
This model doesn't have a readme.
Trained on old Looney tune RoadRunner background art
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 paappraiser/wile_e_coyote_background using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"paappraiser/wile_e_coyote_background:516edc454df224582f278388ca4838a408c98d9b6af2108d0aaf0c36f98a1d33",
{
input: {
width: 1024,
height: 1024,
prompt: "a picture of TOK of a house on a long desert trail ",
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: "realistic",
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 paappraiser/wile_e_coyote_background using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"paappraiser/wile_e_coyote_background:516edc454df224582f278388ca4838a408c98d9b6af2108d0aaf0c36f98a1d33",
input={
"width": 1024,
"height": 1024,
"prompt": "a picture of TOK of a house on a long desert trail ",
"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": "realistic",
"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 paappraiser/wile_e_coyote_background 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": "516edc454df224582f278388ca4838a408c98d9b6af2108d0aaf0c36f98a1d33",
"input": {
"width": 1024,
"height": 1024,
"prompt": "a picture of TOK of a house on a long desert trail ",
"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": "realistic",
"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 paappraiser/wile_e_coyote_background using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/paappraiser/wile_e_coyote_background@sha256:516edc454df224582f278388ca4838a408c98d9b6af2108d0aaf0c36f98a1d33 \
-i 'width=1024' \
-i 'height=1024' \
-i 'prompt="a picture of TOK of a house on a long desert trail "' \
-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="realistic"' \
-i 'prompt_strength=0.8' \
-i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run paappraiser/wile_e_coyote_background 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/paappraiser/wile_e_coyote_background@sha256:516edc454df224582f278388ca4838a408c98d9b6af2108d0aaf0c36f98a1d33
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "a picture of TOK of a house on a long desert trail ", "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": "realistic", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Add a payment method to run this model.
Each run costs approximately $0.016. Alternatively, try out our featured models for free.
By signing in, you agree to our
terms of service and privacy policy
{
"completed_at": "2023-09-06T22:18:00.977435Z",
"created_at": "2023-09-06T22:17:04.017872Z",
"data_removed": false,
"error": null,
"id": "y7stb7dbtebq7t5wgpv5rliecq",
"input": {
"width": 1024,
"height": 1024,
"prompt": "a picture of TOK of a house on a long desert trail ",
"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": "realistic",
"prompt_strength": 0.8,
"num_inference_steps": 50
},
"logs": "Using seed: 48153\nPrompt: a picture of <s0><s1> of a house on a long desert trail\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, 1.96it/s]\n 6%|▌ | 3/50 [00:01<00:18, 2.49it/s]\n 8%|▊ | 4/50 [00:01<00:16, 2.86it/s]\n 10%|█ | 5/50 [00:01<00:14, 3.11it/s]\n 12%|█▏ | 6/50 [00:02<00:13, 3.29it/s]\n 14%|█▍ | 7/50 [00:02<00:12, 3.41it/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, 3.62it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.64it/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, 3.67it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.67it/s]\n 34%|███▍ | 17/50 [00:05<00:08, 3.68it/s]\n 36%|███▌ | 18/50 [00:05<00:08, 3.67it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.68it/s]\n 40%|████ | 20/50 [00:06<00:08, 3.68it/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, 3.70it/s]\n 48%|████▊ | 24/50 [00:07<00:07, 3.70it/s]\n 50%|█████ | 25/50 [00:07<00:06, 3.70it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.70it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.70it/s]\n 56%|█████▌ | 28/50 [00:08<00:05, 3.70it/s]\n 58%|█████▊ | 29/50 [00:08<00:05, 3.70it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.70it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.70it/s]\n 64%|██████▍ | 32/50 [00:09<00:04, 3.70it/s]\n 66%|██████▌ | 33/50 [00:09<00:04, 3.70it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.70it/s]\n 70%|███████ | 35/50 [00:10<00:04, 3.70it/s]\n 72%|███████▏ | 36/50 [00:10<00:03, 3.70it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.70it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.70it/s]\n 78%|███████▊ | 39/50 [00:11<00:02, 3.70it/s]\n 80%|████████ | 40/50 [00:11<00:02, 3.70it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.70it/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, 3.69it/s]\n 94%|█████████▍| 47/50 [00:13<00:00, 3.69it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.69it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.69it/s]\n100%|██████████| 50/50 [00:14<00:00, 3.69it/s]\n100%|██████████| 50/50 [00:14<00:00, 3.54it/s]",
"metrics": {
"predict_time": 16.33587,
"total_time": 56.959563
},
"output": [
"https://replicate.delivery/pbxt/cx6Bv4QIGCJAAtueRWFOQDNPZ7L9GqVHIa4wK3XRzMVMZ1wIA/out-0.png"
],
"started_at": "2023-09-06T22:17:44.641565Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/y7stb7dbtebq7t5wgpv5rliecq",
"cancel": "https://api.replicate.com/v1/predictions/y7stb7dbtebq7t5wgpv5rliecq/cancel"
},
"version": "516edc454df224582f278388ca4838a408c98d9b6af2108d0aaf0c36f98a1d33"
}
Using seed: 48153
Prompt: a picture of <s0><s1> of a house on a long desert trail
txt2img mode
0%| | 0/50 [00:00<?, ?it/s]
2%|▏ | 1/50 [00:00<00:41, 1.17it/s]
4%|▍ | 2/50 [00:01<00:24, 1.96it/s]
6%|▌ | 3/50 [00:01<00:18, 2.49it/s]
8%|▊ | 4/50 [00:01<00:16, 2.86it/s]
10%|█ | 5/50 [00:01<00:14, 3.11it/s]
12%|█▏ | 6/50 [00:02<00:13, 3.29it/s]
14%|█▍ | 7/50 [00:02<00:12, 3.41it/s]
16%|█▌ | 8/50 [00:02<00:12, 3.49it/s]
18%|█▊ | 9/50 [00:03<00:11, 3.55it/s]
20%|██ | 10/50 [00:03<00:11, 3.59it/s]
22%|██▏ | 11/50 [00:03<00:10, 3.62it/s]
24%|██▍ | 12/50 [00:03<00:10, 3.64it/s]
26%|██▌ | 13/50 [00:04<00:10, 3.65it/s]
28%|██▊ | 14/50 [00:04<00:09, 3.66it/s]
30%|███ | 15/50 [00:04<00:09, 3.67it/s]
32%|███▏ | 16/50 [00:04<00:09, 3.67it/s]
34%|███▍ | 17/50 [00:05<00:08, 3.68it/s]
36%|███▌ | 18/50 [00:05<00:08, 3.67it/s]
38%|███▊ | 19/50 [00:05<00:08, 3.68it/s]
40%|████ | 20/50 [00:06<00:08, 3.68it/s]
42%|████▏ | 21/50 [00:06<00:07, 3.69it/s]
44%|████▍ | 22/50 [00:06<00:07, 3.69it/s]
46%|████▌ | 23/50 [00:06<00:07, 3.70it/s]
48%|████▊ | 24/50 [00:07<00:07, 3.70it/s]
50%|█████ | 25/50 [00:07<00:06, 3.70it/s]
52%|█████▏ | 26/50 [00:07<00:06, 3.70it/s]
54%|█████▍ | 27/50 [00:07<00:06, 3.70it/s]
56%|█████▌ | 28/50 [00:08<00:05, 3.70it/s]
58%|█████▊ | 29/50 [00:08<00:05, 3.70it/s]
60%|██████ | 30/50 [00:08<00:05, 3.70it/s]
62%|██████▏ | 31/50 [00:08<00:05, 3.70it/s]
64%|██████▍ | 32/50 [00:09<00:04, 3.70it/s]
66%|██████▌ | 33/50 [00:09<00:04, 3.70it/s]
68%|██████▊ | 34/50 [00:09<00:04, 3.70it/s]
70%|███████ | 35/50 [00:10<00:04, 3.70it/s]
72%|███████▏ | 36/50 [00:10<00:03, 3.70it/s]
74%|███████▍ | 37/50 [00:10<00:03, 3.70it/s]
76%|███████▌ | 38/50 [00:10<00:03, 3.70it/s]
78%|███████▊ | 39/50 [00:11<00:02, 3.70it/s]
80%|████████ | 40/50 [00:11<00:02, 3.70it/s]
82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s]
84%|████████▍ | 42/50 [00:11<00:02, 3.70it/s]
86%|████████▌ | 43/50 [00:12<00:01, 3.69it/s]
88%|████████▊ | 44/50 [00:12<00:01, 3.69it/s]
90%|█████████ | 45/50 [00:12<00:01, 3.69it/s]
92%|█████████▏| 46/50 [00:13<00:01, 3.69it/s]
94%|█████████▍| 47/50 [00:13<00:00, 3.69it/s]
96%|█████████▌| 48/50 [00:13<00:00, 3.69it/s]
98%|█████████▊| 49/50 [00:13<00:00, 3.69it/s]
100%|██████████| 50/50 [00:14<00:00, 3.69it/s]
100%|██████████| 50/50 [00:14<00:00, 3.54it/s]
This model costs approximately $0.016 to run on Replicate, or 62 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 17 seconds.
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: 48153
Prompt: a picture of <s0><s1> of a house on a long desert trail
txt2img mode
0%| | 0/50 [00:00<?, ?it/s]
2%|▏ | 1/50 [00:00<00:41, 1.17it/s]
4%|▍ | 2/50 [00:01<00:24, 1.96it/s]
6%|▌ | 3/50 [00:01<00:18, 2.49it/s]
8%|▊ | 4/50 [00:01<00:16, 2.86it/s]
10%|█ | 5/50 [00:01<00:14, 3.11it/s]
12%|█▏ | 6/50 [00:02<00:13, 3.29it/s]
14%|█▍ | 7/50 [00:02<00:12, 3.41it/s]
16%|█▌ | 8/50 [00:02<00:12, 3.49it/s]
18%|█▊ | 9/50 [00:03<00:11, 3.55it/s]
20%|██ | 10/50 [00:03<00:11, 3.59it/s]
22%|██▏ | 11/50 [00:03<00:10, 3.62it/s]
24%|██▍ | 12/50 [00:03<00:10, 3.64it/s]
26%|██▌ | 13/50 [00:04<00:10, 3.65it/s]
28%|██▊ | 14/50 [00:04<00:09, 3.66it/s]
30%|███ | 15/50 [00:04<00:09, 3.67it/s]
32%|███▏ | 16/50 [00:04<00:09, 3.67it/s]
34%|███▍ | 17/50 [00:05<00:08, 3.68it/s]
36%|███▌ | 18/50 [00:05<00:08, 3.67it/s]
38%|███▊ | 19/50 [00:05<00:08, 3.68it/s]
40%|████ | 20/50 [00:06<00:08, 3.68it/s]
42%|████▏ | 21/50 [00:06<00:07, 3.69it/s]
44%|████▍ | 22/50 [00:06<00:07, 3.69it/s]
46%|████▌ | 23/50 [00:06<00:07, 3.70it/s]
48%|████▊ | 24/50 [00:07<00:07, 3.70it/s]
50%|█████ | 25/50 [00:07<00:06, 3.70it/s]
52%|█████▏ | 26/50 [00:07<00:06, 3.70it/s]
54%|█████▍ | 27/50 [00:07<00:06, 3.70it/s]
56%|█████▌ | 28/50 [00:08<00:05, 3.70it/s]
58%|█████▊ | 29/50 [00:08<00:05, 3.70it/s]
60%|██████ | 30/50 [00:08<00:05, 3.70it/s]
62%|██████▏ | 31/50 [00:08<00:05, 3.70it/s]
64%|██████▍ | 32/50 [00:09<00:04, 3.70it/s]
66%|██████▌ | 33/50 [00:09<00:04, 3.70it/s]
68%|██████▊ | 34/50 [00:09<00:04, 3.70it/s]
70%|███████ | 35/50 [00:10<00:04, 3.70it/s]
72%|███████▏ | 36/50 [00:10<00:03, 3.70it/s]
74%|███████▍ | 37/50 [00:10<00:03, 3.70it/s]
76%|███████▌ | 38/50 [00:10<00:03, 3.70it/s]
78%|███████▊ | 39/50 [00:11<00:02, 3.70it/s]
80%|████████ | 40/50 [00:11<00:02, 3.70it/s]
82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s]
84%|████████▍ | 42/50 [00:11<00:02, 3.70it/s]
86%|████████▌ | 43/50 [00:12<00:01, 3.69it/s]
88%|████████▊ | 44/50 [00:12<00:01, 3.69it/s]
90%|█████████ | 45/50 [00:12<00:01, 3.69it/s]
92%|█████████▏| 46/50 [00:13<00:01, 3.69it/s]
94%|█████████▍| 47/50 [00:13<00:00, 3.69it/s]
96%|█████████▌| 48/50 [00:13<00:00, 3.69it/s]
98%|█████████▊| 49/50 [00:13<00:00, 3.69it/s]
100%|██████████| 50/50 [00:14<00:00, 3.69it/s]
100%|██████████| 50/50 [00:14<00:00, 3.54it/s]