(Updated 9 months, 3 weeks ago)
{
"model": "dev",
"prompt": "black rooster in the style of TOK",
"lora_scale": 1,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"output_quality": 80,
"num_inference_steps": 28
}npm install replicateimport Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run codingfu/bayc using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"codingfu/bayc:d111b63dd1444d142fe8a0c0812ce6796e270f05b791d48d2a5c6296627da82a",
{
input: {
model: "dev",
prompt: "black rooster in the style of TOK",
lora_scale: 1,
num_outputs: 1,
aspect_ratio: "1:1",
output_format: "webp",
guidance_scale: 3.5,
output_quality: 80,
num_inference_steps: 28
}
}
);
// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
pip install replicateimport replicateRun codingfu/bayc using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"codingfu/bayc:d111b63dd1444d142fe8a0c0812ce6796e270f05b791d48d2a5c6296627da82a",
input={
"model": "dev",
"prompt": "black rooster in the style of TOK",
"lora_scale": 1,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"output_quality": 80,
"num_inference_steps": 28
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Run codingfu/bayc 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": "codingfu/bayc:d111b63dd1444d142fe8a0c0812ce6796e270f05b791d48d2a5c6296627da82a",
"input": {
"model": "dev",
"prompt": "black rooster in the style of TOK",
"lora_scale": 1,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"output_quality": 80,
"num_inference_steps": 28
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
{
"completed_at": "2024-08-22T18:35:53.880687Z",
"created_at": "2024-08-22T18:35:06.066000Z",
"data_removed": false,
"error": null,
"id": "by3t857kt9rm00chfdfagf0v4r",
"input": {
"model": "dev",
"prompt": "black rooster in the style of TOK",
"lora_scale": 1,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"output_quality": 80,
"num_inference_steps": 28
},
"logs": "Using seed: 51857\nPrompt: black rooster in the style of TOK\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9781506404352\nDownloading weights\n2024-08-22T18:35:36Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/6421da47ded8c72a url=https://replicate.delivery/yhqm/0jDnFOgloXY9IpHvsM82mSKLWxkt59uYkc3CketKvQ7dtpqJA/trained_model.tar\n2024-08-22T18:35:37Z | INFO | [ Complete ] dest=/src/weights-cache/6421da47ded8c72a size=\"172 MB\" total_elapsed=1.590s url=https://replicate.delivery/yhqm/0jDnFOgloXY9IpHvsM82mSKLWxkt59uYkc3CketKvQ7dtpqJA/trained_model.tar\nb''\nDownloaded weights in 1.6112327575683594 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.69it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.23it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.96it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.79it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.72it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.71it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.69it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.68it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.68it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.71it/s]",
"metrics": {
"predict_time": 17.844050377,
"total_time": 47.814687
},
"output": [
"https://replicate.delivery/yhqm/f4be162dhUlzMEXKUSUnaqOw2OYue0g9efxLjGitpJjLhbqaC/out-0.webp"
],
"started_at": "2024-08-22T18:35:36.036636Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/by3t857kt9rm00chfdfagf0v4r",
"cancel": "https://api.replicate.com/v1/predictions/by3t857kt9rm00chfdfagf0v4r/cancel"
},
"version": "d111b63dd1444d142fe8a0c0812ce6796e270f05b791d48d2a5c6296627da82a"
}Using seed: 51857
Prompt: black rooster in the style of TOK
txt2img mode
Using dev model
Loading LoRA weights
Ensuring enough disk space...
Free disk space: 9781506404352
Downloading weights
2024-08-22T18:35:36Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/6421da47ded8c72a url=https://replicate.delivery/yhqm/0jDnFOgloXY9IpHvsM82mSKLWxkt59uYkc3CketKvQ7dtpqJA/trained_model.tar
2024-08-22T18:35:37Z | INFO | [ Complete ] dest=/src/weights-cache/6421da47ded8c72a size="172 MB" total_elapsed=1.590s url=https://replicate.delivery/yhqm/0jDnFOgloXY9IpHvsM82mSKLWxkt59uYkc3CketKvQ7dtpqJA/trained_model.tar
b''
Downloaded weights in 1.6112327575683594 seconds
LoRA weights loaded successfully
0%| | 0/28 [00:00<?, ?it/s]
4%|▎ | 1/28 [00:00<00:07, 3.69it/s]
7%|▋ | 2/28 [00:00<00:06, 4.23it/s]
11%|█ | 3/28 [00:00<00:06, 3.96it/s]
14%|█▍ | 4/28 [00:01<00:06, 3.85it/s]
18%|█▊ | 5/28 [00:01<00:06, 3.79it/s]
21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]
25%|██▌ | 7/28 [00:01<00:05, 3.72it/s]
29%|██▊ | 8/28 [00:02<00:05, 3.71it/s]
32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]
36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]
39%|███▉ | 11/28 [00:02<00:04, 3.69it/s]
43%|████▎ | 12/28 [00:03<00:04, 3.68it/s]
46%|████▋ | 13/28 [00:03<00:04, 3.68it/s]
50%|█████ | 14/28 [00:03<00:03, 3.68it/s]
54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]
57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s]
61%|██████ | 17/28 [00:04<00:02, 3.68it/s]
64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s]
68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s]
71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s]
75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s]
79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s]
82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s]
86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s]
89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s]
93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s]
96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s]
100%|██████████| 28/28 [00:07<00:00, 3.68it/s]
100%|██████████| 28/28 [00:07<00:00, 3.71it/s]Want to make some of these yourself?
Run this modelThis 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.
Using seed: 51857
Prompt: black rooster in the style of TOK
txt2img mode
Using dev model
Loading LoRA weights
Ensuring enough disk space...
Free disk space: 9781506404352
Downloading weights
2024-08-22T18:35:36Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/6421da47ded8c72a url=https://replicate.delivery/yhqm/0jDnFOgloXY9IpHvsM82mSKLWxkt59uYkc3CketKvQ7dtpqJA/trained_model.tar
2024-08-22T18:35:37Z | INFO | [ Complete ] dest=/src/weights-cache/6421da47ded8c72a size="172 MB" total_elapsed=1.590s url=https://replicate.delivery/yhqm/0jDnFOgloXY9IpHvsM82mSKLWxkt59uYkc3CketKvQ7dtpqJA/trained_model.tar
b''
Downloaded weights in 1.6112327575683594 seconds
LoRA weights loaded successfully
0%| | 0/28 [00:00<?, ?it/s]
4%|▎ | 1/28 [00:00<00:07, 3.69it/s]
7%|▋ | 2/28 [00:00<00:06, 4.23it/s]
11%|█ | 3/28 [00:00<00:06, 3.96it/s]
14%|█▍ | 4/28 [00:01<00:06, 3.85it/s]
18%|█▊ | 5/28 [00:01<00:06, 3.79it/s]
21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]
25%|██▌ | 7/28 [00:01<00:05, 3.72it/s]
29%|██▊ | 8/28 [00:02<00:05, 3.71it/s]
32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]
36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]
39%|███▉ | 11/28 [00:02<00:04, 3.69it/s]
43%|████▎ | 12/28 [00:03<00:04, 3.68it/s]
46%|████▋ | 13/28 [00:03<00:04, 3.68it/s]
50%|█████ | 14/28 [00:03<00:03, 3.68it/s]
54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]
57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s]
61%|██████ | 17/28 [00:04<00:02, 3.68it/s]
64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s]
68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s]
71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s]
75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s]
79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s]
82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s]
86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s]
89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s]
93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s]
96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s]
100%|██████████| 28/28 [00:07<00:00, 3.68it/s]
100%|██████████| 28/28 [00:07<00:00, 3.71it/s]