Readme
This model doesn't have a readme.
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run adminconteudosflix/midjourney-allcraft using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"adminconteudosflix/midjourney-allcraft:40ab9b32cc4584bc069e22027fffb97e79ed550d4e7c20ed6d5d7ef89e8f08f5",
{
input: {
model: "dev",
prompt: "a highly detailed cinematic closeup frontal portrait, humanoid robot with a reflective, dome-shaped head, contains a galaxy cosmos and nebula inside it, the robot's body, in shades of white, purple and black, features an array of textures and protrusions suggesting a complex internal structure, set against a soft-focus background with bokeh effect in cool blue tones, dark environment, moody and epic",
go_fast: true,
lora_scale: 1,
megapixels: "1",
num_outputs: 1,
aspect_ratio: "1:1",
output_format: "webp",
guidance_scale: 3,
output_quality: 100,
prompt_strength: 0.8,
extra_lora_scale: 1,
num_inference_steps: 38
}
}
);
// 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 replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run adminconteudosflix/midjourney-allcraft using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"adminconteudosflix/midjourney-allcraft:40ab9b32cc4584bc069e22027fffb97e79ed550d4e7c20ed6d5d7ef89e8f08f5",
input={
"model": "dev",
"prompt": "a highly detailed cinematic closeup frontal portrait, humanoid robot with a reflective, dome-shaped head, contains a galaxy cosmos and nebula inside it, the robot's body, in shades of white, purple and black, features an array of textures and protrusions suggesting a complex internal structure, set against a soft-focus background with bokeh effect in cool blue tones, dark environment, moody and epic",
"go_fast": True,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 38
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run adminconteudosflix/midjourney-allcraft 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": "adminconteudosflix/midjourney-allcraft:40ab9b32cc4584bc069e22027fffb97e79ed550d4e7c20ed6d5d7ef89e8f08f5",
"input": {
"model": "dev",
"prompt": "a highly detailed cinematic closeup frontal portrait, humanoid robot with a reflective, dome-shaped head, contains a galaxy cosmos and nebula inside it, the robot\'s body, in shades of white, purple and black, features an array of textures and protrusions suggesting a complex internal structure, set against a soft-focus background with bokeh effect in cool blue tones, dark environment, moody and epic",
"go_fast": true,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 38
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
By signing in, you agree to our
terms of service and privacy policy
{
"completed_at": "2025-04-02T04:59:16.791740Z",
"created_at": "2025-04-02T04:59:12.475000Z",
"data_removed": false,
"error": null,
"id": "yn4npdgyvdrma0cnykfbkxhnr8",
"input": {
"model": "dev",
"prompt": "a highly detailed cinematic closeup frontal portrait, humanoid robot with a reflective, dome-shaped head, contains a galaxy cosmos and nebula inside it, the robot's body, in shades of white, purple and black, features an array of textures and protrusions suggesting a complex internal structure, set against a soft-focus background with bokeh effect in cool blue tones, dark environment, moody and epic",
"go_fast": true,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 38
},
"logs": "2025-04-02 04:59:12.518 | INFO | fp8.lora_loading:restore_base_weights:600 - Unloaded 304 layers\n2025-04-02 04:59:12.520 | SUCCESS | fp8.lora_loading:unload_loras:571 - LoRAs unloaded in 0.023s\n2025-04-02 04:59:12.520 | INFO | fp8.lora_loading:convert_lora_weights:502 - Loading LoRA weights for /src/weights-cache/44112deb614f0d96\n2025-04-02 04:59:12.683 | INFO | fp8.lora_loading:convert_lora_weights:523 - LoRA weights loaded\n2025-04-02 04:59:12.683 | DEBUG | fp8.lora_loading:apply_lora_to_model_and_optionally_store_clones:610 - Extracting keys\n2025-04-02 04:59:12.683 | DEBUG | fp8.lora_loading:apply_lora_to_model_and_optionally_store_clones:617 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 44%|████▍ | 135/304 [00:00<00:00, 1337.27it/s]\nApplying LoRA: 88%|████████▊ | 269/304 [00:00<00:00, 1047.41it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 1067.35it/s]\n2025-04-02 04:59:12.969 | INFO | fp8.lora_loading:apply_lora_to_model_and_optionally_store_clones:669 - Loading LoRA in fp8\n2025-04-02 04:59:12.969 | SUCCESS | fp8.lora_loading:load_lora:547 - LoRA applied in 0.45s\nrunning quantized prediction\nUsing seed: 1120804906\n 0%| | 0/38 [00:00<?, ?it/s]\n 8%|▊ | 3/38 [00:00<00:02, 16.09it/s]\n 13%|█▎ | 5/38 [00:00<00:02, 13.06it/s]\n 18%|█▊ | 7/38 [00:00<00:02, 12.10it/s]\n 24%|██▎ | 9/38 [00:00<00:02, 11.61it/s]\n 29%|██▉ | 11/38 [00:00<00:02, 11.09it/s]\n 34%|███▍ | 13/38 [00:01<00:02, 10.89it/s]\n 39%|███▉ | 15/38 [00:01<00:02, 10.88it/s]\n 45%|████▍ | 17/38 [00:01<00:01, 10.88it/s]\n 50%|█████ | 19/38 [00:01<00:01, 10.88it/s]\n 55%|█████▌ | 21/38 [00:01<00:01, 10.79it/s]\n 61%|██████ | 23/38 [00:02<00:01, 10.70it/s]\n 66%|██████▌ | 25/38 [00:02<00:01, 10.71it/s]\n 71%|███████ | 27/38 [00:02<00:01, 10.76it/s]\n 76%|███████▋ | 29/38 [00:02<00:00, 10.81it/s]\n 82%|████████▏ | 31/38 [00:02<00:00, 10.75it/s]\n 87%|████████▋ | 33/38 [00:02<00:00, 10.70it/s]\n 92%|█████████▏| 35/38 [00:03<00:00, 10.69it/s]\n 97%|█████████▋| 37/38 [00:03<00:00, 10.72it/s]\n100%|██████████| 38/38 [00:03<00:00, 11.02it/s]\nTotal safe images: 1 out of 1",
"metrics": {
"predict_time": 4.294354319,
"total_time": 4.31674
},
"output": [
"https://replicate.delivery/xezq/98efrLgtDWnGfoNVAJrmfF7A8vAXyIeZmejGQ2TYdFfFSsTPKA/out-0.webp"
],
"started_at": "2025-04-02T04:59:12.497385Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-tkn3kwdaerqnoasfm5xup33cb2kda4lp5a4guok6jeq5hklplzvq",
"get": "https://api.replicate.com/v1/predictions/yn4npdgyvdrma0cnykfbkxhnr8",
"cancel": "https://api.replicate.com/v1/predictions/yn4npdgyvdrma0cnykfbkxhnr8/cancel"
},
"version": "40ab9b32cc4584bc069e22027fffb97e79ed550d4e7c20ed6d5d7ef89e8f08f5"
}
2025-04-02 04:59:12.518 | INFO | fp8.lora_loading:restore_base_weights:600 - Unloaded 304 layers
2025-04-02 04:59:12.520 | SUCCESS | fp8.lora_loading:unload_loras:571 - LoRAs unloaded in 0.023s
2025-04-02 04:59:12.520 | INFO | fp8.lora_loading:convert_lora_weights:502 - Loading LoRA weights for /src/weights-cache/44112deb614f0d96
2025-04-02 04:59:12.683 | INFO | fp8.lora_loading:convert_lora_weights:523 - LoRA weights loaded
2025-04-02 04:59:12.683 | DEBUG | fp8.lora_loading:apply_lora_to_model_and_optionally_store_clones:610 - Extracting keys
2025-04-02 04:59:12.683 | DEBUG | fp8.lora_loading:apply_lora_to_model_and_optionally_store_clones:617 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 44%|████▍ | 135/304 [00:00<00:00, 1337.27it/s]
Applying LoRA: 88%|████████▊ | 269/304 [00:00<00:00, 1047.41it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 1067.35it/s]
2025-04-02 04:59:12.969 | INFO | fp8.lora_loading:apply_lora_to_model_and_optionally_store_clones:669 - Loading LoRA in fp8
2025-04-02 04:59:12.969 | SUCCESS | fp8.lora_loading:load_lora:547 - LoRA applied in 0.45s
running quantized prediction
Using seed: 1120804906
0%| | 0/38 [00:00<?, ?it/s]
8%|▊ | 3/38 [00:00<00:02, 16.09it/s]
13%|█▎ | 5/38 [00:00<00:02, 13.06it/s]
18%|█▊ | 7/38 [00:00<00:02, 12.10it/s]
24%|██▎ | 9/38 [00:00<00:02, 11.61it/s]
29%|██▉ | 11/38 [00:00<00:02, 11.09it/s]
34%|███▍ | 13/38 [00:01<00:02, 10.89it/s]
39%|███▉ | 15/38 [00:01<00:02, 10.88it/s]
45%|████▍ | 17/38 [00:01<00:01, 10.88it/s]
50%|█████ | 19/38 [00:01<00:01, 10.88it/s]
55%|█████▌ | 21/38 [00:01<00:01, 10.79it/s]
61%|██████ | 23/38 [00:02<00:01, 10.70it/s]
66%|██████▌ | 25/38 [00:02<00:01, 10.71it/s]
71%|███████ | 27/38 [00:02<00:01, 10.76it/s]
76%|███████▋ | 29/38 [00:02<00:00, 10.81it/s]
82%|████████▏ | 31/38 [00:02<00:00, 10.75it/s]
87%|████████▋ | 33/38 [00:02<00:00, 10.70it/s]
92%|█████████▏| 35/38 [00:03<00:00, 10.69it/s]
97%|█████████▋| 37/38 [00:03<00:00, 10.72it/s]
100%|██████████| 38/38 [00:03<00:00, 11.02it/s]
Total safe images: 1 out of 1
This model costs approximately $0.017 to run on Replicate, or 58 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 H100 GPU hardware. Predictions typically complete within 12 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
2025-04-02 04:59:12.518 | INFO | fp8.lora_loading:restore_base_weights:600 - Unloaded 304 layers
2025-04-02 04:59:12.520 | SUCCESS | fp8.lora_loading:unload_loras:571 - LoRAs unloaded in 0.023s
2025-04-02 04:59:12.520 | INFO | fp8.lora_loading:convert_lora_weights:502 - Loading LoRA weights for /src/weights-cache/44112deb614f0d96
2025-04-02 04:59:12.683 | INFO | fp8.lora_loading:convert_lora_weights:523 - LoRA weights loaded
2025-04-02 04:59:12.683 | DEBUG | fp8.lora_loading:apply_lora_to_model_and_optionally_store_clones:610 - Extracting keys
2025-04-02 04:59:12.683 | DEBUG | fp8.lora_loading:apply_lora_to_model_and_optionally_store_clones:617 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 44%|████▍ | 135/304 [00:00<00:00, 1337.27it/s]
Applying LoRA: 88%|████████▊ | 269/304 [00:00<00:00, 1047.41it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 1067.35it/s]
2025-04-02 04:59:12.969 | INFO | fp8.lora_loading:apply_lora_to_model_and_optionally_store_clones:669 - Loading LoRA in fp8
2025-04-02 04:59:12.969 | SUCCESS | fp8.lora_loading:load_lora:547 - LoRA applied in 0.45s
running quantized prediction
Using seed: 1120804906
0%| | 0/38 [00:00<?, ?it/s]
8%|▊ | 3/38 [00:00<00:02, 16.09it/s]
13%|█▎ | 5/38 [00:00<00:02, 13.06it/s]
18%|█▊ | 7/38 [00:00<00:02, 12.10it/s]
24%|██▎ | 9/38 [00:00<00:02, 11.61it/s]
29%|██▉ | 11/38 [00:00<00:02, 11.09it/s]
34%|███▍ | 13/38 [00:01<00:02, 10.89it/s]
39%|███▉ | 15/38 [00:01<00:02, 10.88it/s]
45%|████▍ | 17/38 [00:01<00:01, 10.88it/s]
50%|█████ | 19/38 [00:01<00:01, 10.88it/s]
55%|█████▌ | 21/38 [00:01<00:01, 10.79it/s]
61%|██████ | 23/38 [00:02<00:01, 10.70it/s]
66%|██████▌ | 25/38 [00:02<00:01, 10.71it/s]
71%|███████ | 27/38 [00:02<00:01, 10.76it/s]
76%|███████▋ | 29/38 [00:02<00:00, 10.81it/s]
82%|████████▏ | 31/38 [00:02<00:00, 10.75it/s]
87%|████████▋ | 33/38 [00:02<00:00, 10.70it/s]
92%|█████████▏| 35/38 [00:03<00:00, 10.69it/s]
97%|█████████▋| 37/38 [00:03<00:00, 10.72it/s]
100%|██████████| 38/38 [00:03<00:00, 11.02it/s]
Total safe images: 1 out of 1