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 mdzor/weapons-items using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"mdzor/weapons-items:4792efc4be50e9b63563a2cd82bea9016c90fcc03c510a5a7b79ee215d685c04",
{
input: {
width: 1024,
height: 1024,
prompt: "TOK, a chest, with gold coins inside",
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: "",
prompt_strength: 0.8,
num_inference_steps: 50
}
}
);
// 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 mdzor/weapons-items using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"mdzor/weapons-items:4792efc4be50e9b63563a2cd82bea9016c90fcc03c510a5a7b79ee215d685c04",
input={
"width": 1024,
"height": 1024,
"prompt": "TOK, a chest, with gold coins inside",
"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": "",
"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 variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run mdzor/weapons-items 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": "mdzor/weapons-items:4792efc4be50e9b63563a2cd82bea9016c90fcc03c510a5a7b79ee215d685c04",
"input": {
"width": 1024,
"height": 1024,
"prompt": "TOK, a chest, with gold coins inside",
"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": "",
"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.
Add a payment method to run this model.
By signing in, you agree to our
terms of service and privacy policy
{
"completed_at": "2024-05-01T02:16:34.897461Z",
"created_at": "2024-05-01T02:16:11.052000Z",
"data_removed": false,
"error": null,
"id": "v22vdh0y5hrgp0cf67r9t42ctg",
"input": {
"width": 1024,
"height": 1024,
"prompt": "TOK, a chest, with gold coins inside",
"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": "",
"prompt_strength": 0.8,
"num_inference_steps": 50
},
"logs": "Using seed: 34657\nEnsuring enough disk space...\nFree disk space: 1777953435648\nDownloading weights: https://replicate.delivery/pbxt/mNeiwD6PA9z5Y6nT9lWAuZPj1MpRdaRBJGQRDhwHl25Wu6XJA/trained_model.tar\n2024-05-01T02:16:14Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/0056b97031f9baf3 url=https://replicate.delivery/pbxt/mNeiwD6PA9z5Y6nT9lWAuZPj1MpRdaRBJGQRDhwHl25Wu6XJA/trained_model.tar\n2024-05-01T02:16:19Z | INFO | [ Complete ] dest=/src/weights-cache/0056b97031f9baf3 size=\"186 MB\" total_elapsed=4.378s url=https://replicate.delivery/pbxt/mNeiwD6PA9z5Y6nT9lWAuZPj1MpRdaRBJGQRDhwHl25Wu6XJA/trained_model.tar\nb''\nDownloaded weights in 4.528833627700806 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: <s0><s1>, a chest, with gold coins inside\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.67it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.66it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.67it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.67it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.67it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.67it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.67it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.67it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.67it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.67it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.67it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.67it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.67it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.67it/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 [00:04<00:09, 3.67it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.67it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.67it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.67it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.67it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.66it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.66it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.66it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.66it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.66it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.66it/s]\n 56%|█████▌ | 28/50 [00:07<00:06, 3.66it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.66it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.65it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.65it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.65it/s]\n 66%|██████▌ | 33/50 [00:09<00:04, 3.65it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.65it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.65it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.65it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.65it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.65it/s]\n 78%|███████▊ | 39/50 [00:10<00:03, 3.65it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.65it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.65it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.65it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.65it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.64it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.64it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.64it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.64it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.64it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.64it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.65it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.66it/s]",
"metrics": {
"predict_time": 20.194817,
"total_time": 23.845461
},
"output": [
"https://replicate.delivery/pbxt/OLEtrz1xt1YjLt3E0w7o2SK8IQdu9Z1oIj2ppQGI8TrAY9rE/out-0.png"
],
"started_at": "2024-05-01T02:16:14.702644Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/v22vdh0y5hrgp0cf67r9t42ctg",
"cancel": "https://api.replicate.com/v1/predictions/v22vdh0y5hrgp0cf67r9t42ctg/cancel"
},
"version": "da029eb60bea4362bb19c04b9d6039d225dd1a661242b71fa6b1866b6ae88c57"
}
Using seed: 34657
Ensuring enough disk space...
Free disk space: 1777953435648
Downloading weights: https://replicate.delivery/pbxt/mNeiwD6PA9z5Y6nT9lWAuZPj1MpRdaRBJGQRDhwHl25Wu6XJA/trained_model.tar
2024-05-01T02:16:14Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/0056b97031f9baf3 url=https://replicate.delivery/pbxt/mNeiwD6PA9z5Y6nT9lWAuZPj1MpRdaRBJGQRDhwHl25Wu6XJA/trained_model.tar
2024-05-01T02:16:19Z | INFO | [ Complete ] dest=/src/weights-cache/0056b97031f9baf3 size="186 MB" total_elapsed=4.378s url=https://replicate.delivery/pbxt/mNeiwD6PA9z5Y6nT9lWAuZPj1MpRdaRBJGQRDhwHl25Wu6XJA/trained_model.tar
b''
Downloaded weights in 4.528833627700806 seconds
Loading fine-tuned model
Does not have Unet. assume we are using LoRA
Loading Unet LoRA
Prompt: <s0><s1>, a chest, with gold coins inside
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This output was created using a different version of the model, mdzor/weapons-items:da029eb6.
This model costs approximately $0.0082 to run on Replicate, or 121 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 9 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.
This model costs approximately $0.0082 to run on Replicate, but this varies depending on your inputs. View more.
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: 34657
Ensuring enough disk space...
Free disk space: 1777953435648
Downloading weights: https://replicate.delivery/pbxt/mNeiwD6PA9z5Y6nT9lWAuZPj1MpRdaRBJGQRDhwHl25Wu6XJA/trained_model.tar
2024-05-01T02:16:14Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/0056b97031f9baf3 url=https://replicate.delivery/pbxt/mNeiwD6PA9z5Y6nT9lWAuZPj1MpRdaRBJGQRDhwHl25Wu6XJA/trained_model.tar
2024-05-01T02:16:19Z | INFO | [ Complete ] dest=/src/weights-cache/0056b97031f9baf3 size="186 MB" total_elapsed=4.378s url=https://replicate.delivery/pbxt/mNeiwD6PA9z5Y6nT9lWAuZPj1MpRdaRBJGQRDhwHl25Wu6XJA/trained_model.tar
b''
Downloaded weights in 4.528833627700806 seconds
Loading fine-tuned model
Does not have Unet. assume we are using LoRA
Loading Unet LoRA
Prompt: <s0><s1>, a chest, with gold coins inside
txt2img mode
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