{
"model": "dev",
"width": 1440,
"height": 1440,
"prompt": "an ECAL student eating noodles in the style of MKB",
"lora_scale": 1.19,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "png",
"guidance_scale": 3.5,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"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 marcodemutiis/mukbang using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"marcodemutiis/mukbang:5294714ceca9ef3dc2ddd8191d54ab69bbcfa90c24477a64e4a7e13692dea481",
{
input: {
model: "dev",
width: 1440,
height: 1440,
prompt: "an ECAL student eating noodles in the style of MKB",
lora_scale: 1.19,
num_outputs: 1,
aspect_ratio: "1:1",
output_format: "png",
guidance_scale: 3.5,
output_quality: 100,
prompt_strength: 0.8,
extra_lora_scale: 1,
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 marcodemutiis/mukbang using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"marcodemutiis/mukbang:5294714ceca9ef3dc2ddd8191d54ab69bbcfa90c24477a64e4a7e13692dea481",
input={
"model": "dev",
"width": 1440,
"height": 1440,
"prompt": "an ECAL student eating noodles in the style of MKB",
"lora_scale": 1.19,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "png",
"guidance_scale": 3.5,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
)
# To access the file URL:
print(output[0].url())
#=> "http://example.com"
# To write the file to disk:
with open("my-image.png", "wb") as file:
file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run marcodemutiis/mukbang 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": "marcodemutiis/mukbang:5294714ceca9ef3dc2ddd8191d54ab69bbcfa90c24477a64e4a7e13692dea481",
"input": {
"model": "dev",
"width": 1440,
"height": 1440,
"prompt": "an ECAL student eating noodles in the style of MKB",
"lora_scale": 1.19,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "png",
"guidance_scale": 3.5,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
{
"completed_at": "2024-09-23T15:18:32.858162Z",
"created_at": "2024-09-23T15:18:08.413000Z",
"data_removed": false,
"error": null,
"id": "58sz8h913nrm40cj3xv8xnfx9w",
"input": {
"model": "dev",
"width": 1440,
"height": 1440,
"prompt": "an ECAL student eating noodles in the style of MKB",
"lora_scale": 1.19,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "png",
"guidance_scale": 3.5,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
},
"logs": "Using seed: 10958\nPrompt: an ECAL student eating noodles in the style of MKB\n[!] txt2img mode\nUsing dev model\nfree=6470518317056\nDownloading weights\n2024-09-23T15:18:08Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpk25a8k4k/weights url=https://replicate.delivery/yhqm/8CkfXeruifdlnImKa77xrf7bk6LHGb8e3cjR51ZUnl5Ynae3E/trained_model.tar\n2024-09-23T15:18:11Z | INFO | [ Complete ] dest=/tmp/tmpk25a8k4k/weights size=\"172 MB\" total_elapsed=2.514s url=https://replicate.delivery/yhqm/8CkfXeruifdlnImKa77xrf7bk6LHGb8e3cjR51ZUnl5Ynae3E/trained_model.tar\nDownloaded weights in 2.61s\nLoaded LoRAs in 15.64s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.41it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.77it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.65it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.59it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.56it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.54it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.53it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.52it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.51it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.51it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.51it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.50it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.50it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.51it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.51it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.51it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.50it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.50it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.51it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.51it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.50it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.50it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.50it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.50it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.50it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.51it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.51it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.50it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.52it/s]",
"metrics": {
"predict_time": 24.436128912,
"total_time": 24.445162
},
"output": [
"https://replicate.delivery/yhqm/Utt1js7ydsYfUahFLEucajhmlZfprZVYNn1Hq9ibH18IjzfmA/out-0.png"
],
"started_at": "2024-09-23T15:18:08.422033Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/58sz8h913nrm40cj3xv8xnfx9w",
"cancel": "https://api.replicate.com/v1/predictions/58sz8h913nrm40cj3xv8xnfx9w/cancel"
},
"version": "5294714ceca9ef3dc2ddd8191d54ab69bbcfa90c24477a64e4a7e13692dea481"
}Using seed: 10958
Prompt: an ECAL student eating noodles in the style of MKB
[!] txt2img mode
Using dev model
free=6470518317056
Downloading weights
2024-09-23T15:18:08Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpk25a8k4k/weights url=https://replicate.delivery/yhqm/8CkfXeruifdlnImKa77xrf7bk6LHGb8e3cjR51ZUnl5Ynae3E/trained_model.tar
2024-09-23T15:18:11Z | INFO | [ Complete ] dest=/tmp/tmpk25a8k4k/weights size="172 MB" total_elapsed=2.514s url=https://replicate.delivery/yhqm/8CkfXeruifdlnImKa77xrf7bk6LHGb8e3cjR51ZUnl5Ynae3E/trained_model.tar
Downloaded weights in 2.61s
Loaded LoRAs in 15.64s
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100%|██████████| 28/28 [00:07<00:00, 3.52it/s]Want to make some of these yourself?
Run this modelThis model is booted and ready for API calls.
This model runs on H100.
Using seed: 10958
Prompt: an ECAL student eating noodles in the style of MKB
[!] txt2img mode
Using dev model
free=6470518317056
Downloading weights
2024-09-23T15:18:08Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpk25a8k4k/weights url=https://replicate.delivery/yhqm/8CkfXeruifdlnImKa77xrf7bk6LHGb8e3cjR51ZUnl5Ynae3E/trained_model.tar
2024-09-23T15:18:11Z | INFO | [ Complete ] dest=/tmp/tmpk25a8k4k/weights size="172 MB" total_elapsed=2.514s url=https://replicate.delivery/yhqm/8CkfXeruifdlnImKa77xrf7bk6LHGb8e3cjR51ZUnl5Ynae3E/trained_model.tar
Downloaded weights in 2.61s
Loaded LoRAs in 15.64s
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