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Input
Run this model in Node.js with one line of code:
npx create-replicate --model=chenxwh/meissonic
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21",
{
input: {
prompt: "a photo of an astronaut riding a horse on mars",
guidance_scale: 9,
negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark",
num_inference_steps: 64
}
}
);
// To access the file URL:
console.log(output.url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:
pip install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21",
input={
"prompt": "a photo of an astronaut riding a horse on mars",
"guidance_scale": 9,
"negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark",
"num_inference_steps": 64
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21",
"input": {
"prompt": "a photo of an astronaut riding a horse on mars",
"guidance_scale": 9,
"negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark",
"num_inference_steps": 64
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
Sign in with GitHub
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terms of service and privacy policy
Output
{
"completed_at": "2024-10-20T19:31:33.131320Z",
"created_at": "2024-10-20T19:28:43.630000Z",
"data_removed": false,
"error": null,
"id": "xmnt06t0dsrgj0cjndkv7try1c",
"input": {
"prompt": "a photo of an astronaut riding a horse on mars",
"guidance_scale": 9,
"negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark",
"num_inference_steps": 64
},
"logs": "Using seed: 43882\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:31, 2.02it/s]\n 3%|▎ | 2/64 [00:00<00:21, 2.94it/s]\n 5%|▍ | 3/64 [00:00<00:17, 3.43it/s]\n 6%|▋ | 4/64 [00:01<00:16, 3.72it/s]\n 8%|▊ | 5/64 [00:01<00:15, 3.90it/s]\n 9%|▉ | 6/64 [00:01<00:14, 4.02it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.10it/s]\n 12%|█▎ | 8/64 [00:02<00:13, 4.16it/s]\n 14%|█▍ | 9/64 [00:02<00:13, 4.19it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.22it/s]\n 17%|█▋ | 11/64 [00:02<00:12, 4.24it/s]\n 19%|█▉ | 12/64 [00:03<00:12, 4.25it/s]\n 20%|██ | 13/64 [00:03<00:11, 4.25it/s]\n 22%|██▏ | 14/64 [00:03<00:11, 4.18it/s]\n 23%|██▎ | 15/64 [00:03<00:11, 4.21it/s]\n 25%|██▌ | 16/64 [00:04<00:11, 4.23it/s]\n 27%|██▋ | 17/64 [00:04<00:11, 4.24it/s]\n 28%|██▊ | 18/64 [00:04<00:10, 4.25it/s]\n 30%|██▉ | 19/64 [00:04<00:10, 4.26it/s]\n 31%|███▏ | 20/64 [00:04<00:10, 4.26it/s]\n 33%|███▎ | 21/64 [00:05<00:10, 4.26it/s]\n 34%|███▍ | 22/64 [00:05<00:09, 4.26it/s]\n 36%|███▌ | 23/64 [00:05<00:09, 4.26it/s]\n 38%|███▊ | 24/64 [00:05<00:09, 4.26it/s]\n 39%|███▉ | 25/64 [00:06<00:09, 4.25it/s]\n 41%|████ | 26/64 [00:06<00:08, 4.26it/s]\n 42%|████▏ | 27/64 [00:06<00:08, 4.26it/s]\n 44%|████▍ | 28/64 [00:06<00:08, 4.26it/s]\n 45%|████▌ | 29/64 [00:07<00:08, 4.26it/s]\n 47%|████▋ | 30/64 [00:07<00:07, 4.26it/s]\n 48%|████▊ | 31/64 [00:07<00:09, 3.42it/s]\n 50%|█████ | 32/64 [00:08<00:09, 3.40it/s]\n 52%|█████▏ | 33/64 [00:08<00:08, 3.62it/s]\n 53%|█████▎ | 34/64 [00:08<00:07, 3.79it/s]\n 55%|█████▍ | 35/64 [00:08<00:07, 3.91it/s]\n 56%|█████▋ | 36/64 [00:08<00:06, 4.01it/s]\n 58%|█████▊ | 37/64 [00:09<00:06, 4.07it/s]\n 59%|█████▉ | 38/64 [00:09<00:06, 4.12it/s]\n 61%|██████ | 39/64 [00:09<00:06, 4.16it/s]\n 62%|██████▎ | 40/64 [00:09<00:05, 4.19it/s]\n 64%|██████▍ | 41/64 [00:10<00:05, 4.21it/s]\n 66%|██████▌ | 42/64 [00:10<00:05, 4.22it/s]\n 67%|██████▋ | 43/64 [00:10<00:04, 4.23it/s]\n 69%|██████▉ | 44/64 [00:10<00:04, 4.24it/s]\n 70%|███████ | 45/64 [00:11<00:04, 4.24it/s]\n 72%|███████▏ | 46/64 [00:11<00:04, 4.24it/s]\n 73%|███████▎ | 47/64 [00:11<00:04, 4.24it/s]\n 75%|███████▌ | 48/64 [00:11<00:03, 4.22it/s]\n 77%|███████▋ | 49/64 [00:12<00:03, 4.23it/s]\n 78%|███████▊ | 50/64 [00:12<00:03, 4.24it/s]\n 80%|███████▉ | 51/64 [00:12<00:03, 4.24it/s]\n 81%|████████▏ | 52/64 [00:12<00:02, 4.24it/s]\n 83%|████████▎ | 53/64 [00:12<00:02, 4.24it/s]\n 84%|████████▍ | 54/64 [00:13<00:02, 4.24it/s]\n 86%|████████▌ | 55/64 [00:13<00:02, 4.25it/s]\n 88%|████████▊ | 56/64 [00:13<00:01, 4.25it/s]\n 89%|████████▉ | 57/64 [00:13<00:01, 4.25it/s]\n 91%|█████████ | 58/64 [00:14<00:01, 4.25it/s]\n 92%|█████████▏| 59/64 [00:14<00:01, 4.24it/s]\n 94%|█████████▍| 60/64 [00:14<00:00, 4.24it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.24it/s]\n 97%|█████████▋| 62/64 [00:15<00:00, 4.23it/s]\n 98%|█████████▊| 63/64 [00:15<00:00, 4.24it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.25it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.11it/s]",
"metrics": {
"predict_time": 18.370107867,
"total_time": 169.50132
},
"output": "https://replicate.delivery/pbxt/tWEHQdPsnuqPOZrcbbZmLDqYZTrFZIappz8k0Wgp0l1kMM6E/out.png",
"started_at": "2024-10-20T19:31:14.761212Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/xmnt06t0dsrgj0cjndkv7try1c",
"cancel": "https://api.replicate.com/v1/predictions/xmnt06t0dsrgj0cjndkv7try1c/cancel"
},
"version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21"
}Generated in
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