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 codelace/nocaptions3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"codelace/nocaptions3:699912703d8dd9762877ff8d693a808a2e089bf74534fad1acb31e43b2e79f0b",
{
input: {
mask: "https://replicate.delivery/pbxt/MN2qW6TxHNOpEDF3g1CKrbQSrKF2Nn9g7RUB30Xes1WxKnEH/lady_002_vanilla_mask.png",
image: "https://replicate.delivery/pbxt/MN2qWKDYehoE3rsfsOPY4f3pGXNH0HXrqKgdjjWZqpwuUnSH/lady_002_vanilla.png",
model: "dev",
prompt: "BespokePunksStyle",
go_fast: false,
lora_scale: 1,
megapixels: "1",
num_outputs: 1,
aspect_ratio: "1:1",
output_format: "jpg",
guidance_scale: 9.58,
output_quality: 80,
prompt_strength: 1,
extra_lora_scale: 1,
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 codelace/nocaptions3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"codelace/nocaptions3:699912703d8dd9762877ff8d693a808a2e089bf74534fad1acb31e43b2e79f0b",
input={
"mask": "https://replicate.delivery/pbxt/MN2qW6TxHNOpEDF3g1CKrbQSrKF2Nn9g7RUB30Xes1WxKnEH/lady_002_vanilla_mask.png",
"image": "https://replicate.delivery/pbxt/MN2qWKDYehoE3rsfsOPY4f3pGXNH0HXrqKgdjjWZqpwuUnSH/lady_002_vanilla.png",
"model": "dev",
"prompt": "BespokePunksStyle",
"go_fast": False,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "jpg",
"guidance_scale": 9.58,
"output_quality": 80,
"prompt_strength": 1,
"extra_lora_scale": 1,
"num_inference_steps": 50
}
)
# 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.
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run codelace/nocaptions3 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": "codelace/nocaptions3:699912703d8dd9762877ff8d693a808a2e089bf74534fad1acb31e43b2e79f0b",
"input": {
"mask": "https://replicate.delivery/pbxt/MN2qW6TxHNOpEDF3g1CKrbQSrKF2Nn9g7RUB30Xes1WxKnEH/lady_002_vanilla_mask.png",
"image": "https://replicate.delivery/pbxt/MN2qWKDYehoE3rsfsOPY4f3pGXNH0HXrqKgdjjWZqpwuUnSH/lady_002_vanilla.png",
"model": "dev",
"prompt": "BespokePunksStyle",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "jpg",
"guidance_scale": 9.58,
"output_quality": 80,
"prompt_strength": 1,
"extra_lora_scale": 1,
"num_inference_steps": 50
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/codelace/nocaptions3@sha256:699912703d8dd9762877ff8d693a808a2e089bf74534fad1acb31e43b2e79f0b \
-i 'mask="https://replicate.delivery/pbxt/MN2qW6TxHNOpEDF3g1CKrbQSrKF2Nn9g7RUB30Xes1WxKnEH/lady_002_vanilla_mask.png"' \
-i 'image="https://replicate.delivery/pbxt/MN2qWKDYehoE3rsfsOPY4f3pGXNH0HXrqKgdjjWZqpwuUnSH/lady_002_vanilla.png"' \
-i 'model="dev"' \
-i 'prompt="BespokePunksStyle"' \
-i 'go_fast=false' \
-i 'lora_scale=1' \
-i 'megapixels="1"' \
-i 'num_outputs=1' \
-i 'aspect_ratio="1:1"' \
-i 'output_format="jpg"' \
-i 'guidance_scale=9.58' \
-i 'output_quality=80' \
-i 'prompt_strength=1' \
-i 'extra_lora_scale=1' \
-i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/codelace/nocaptions3@sha256:699912703d8dd9762877ff8d693a808a2e089bf74534fad1acb31e43b2e79f0b
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "mask": "https://replicate.delivery/pbxt/MN2qW6TxHNOpEDF3g1CKrbQSrKF2Nn9g7RUB30Xes1WxKnEH/lady_002_vanilla_mask.png", "image": "https://replicate.delivery/pbxt/MN2qWKDYehoE3rsfsOPY4f3pGXNH0HXrqKgdjjWZqpwuUnSH/lady_002_vanilla.png", "model": "dev", "prompt": "BespokePunksStyle", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 9.58, "output_quality": 80, "prompt_strength": 1, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
By signing in, you agree to our
terms of service and privacy policy
{
"completed_at": "2025-01-23T08:32:54.537750Z",
"created_at": "2025-01-23T08:32:46.913000Z",
"data_removed": false,
"error": null,
"id": "pr0ewnev85rme0cmj95at7xwmm",
"input": {
"mask": "https://replicate.delivery/pbxt/MN2qW6TxHNOpEDF3g1CKrbQSrKF2Nn9g7RUB30Xes1WxKnEH/lady_002_vanilla_mask.png",
"image": "https://replicate.delivery/pbxt/MN2qWKDYehoE3rsfsOPY4f3pGXNH0HXrqKgdjjWZqpwuUnSH/lady_002_vanilla.png",
"model": "dev",
"prompt": "BespokePunksStyle",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "jpg",
"guidance_scale": 9.58,
"output_quality": 80,
"prompt_strength": 1,
"extra_lora_scale": 1,
"num_inference_steps": 50
},
"logs": "2025-01-23 08:32:47.403 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-23 08:32:47.404 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2778.88it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2650.84it/s]\n2025-01-23 08:32:47.519 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s\nfree=29127590260736\nDownloading weights\n2025-01-23T08:32:47Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpj7glogp9/weights url=https://replicate.delivery/xezq/MKoZRVQ88p6dGhP6vUETXATQDGVufyleGAP9YnjkgfuXg1LoA/trained_model.tar\n2025-01-23T08:32:49Z | INFO | [ Complete ] dest=/tmp/tmpj7glogp9/weights size=\"344 MB\" total_elapsed=2.394s url=https://replicate.delivery/xezq/MKoZRVQ88p6dGhP6vUETXATQDGVufyleGAP9YnjkgfuXg1LoA/trained_model.tar\nDownloaded weights in 2.42s\n2025-01-23 08:32:49.939 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/67225bfb7e57db18\n2025-01-23 08:32:50.052 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-23 08:32:50.053 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-23 08:32:50.053 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2779.57it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2651.48it/s]\n2025-01-23 08:32:50.168 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s\nUsing seed: 21209\nImage detected - setting to img2img mode\nInput image size: 576x576\nInput image size set to: 576x576\n0it [00:00, ?it/s]\n2it [00:00, 16.28it/s]\n4it [00:00, 14.26it/s]\n6it [00:00, 13.74it/s]\n8it [00:00, 13.51it/s]\n10it [00:00, 13.36it/s]\n12it [00:00, 13.27it/s]\n14it [00:01, 13.22it/s]\n16it [00:01, 13.18it/s]\n18it [00:01, 13.15it/s]\n20it [00:01, 13.14it/s]\n22it [00:01, 13.11it/s]\n24it [00:01, 13.11it/s]\n26it [00:01, 13.10it/s]\n28it [00:02, 13.10it/s]\n30it [00:02, 13.11it/s]\n32it [00:02, 13.13it/s]\n34it [00:02, 13.13it/s]\n36it [00:02, 13.12it/s]\n38it [00:02, 13.12it/s]\n40it [00:03, 13.13it/s]\n42it [00:03, 13.11it/s]\n44it [00:03, 13.12it/s]\n46it [00:03, 13.12it/s]\n48it [00:03, 13.13it/s]\n50it [00:03, 13.13it/s]\n50it [00:03, 13.22it/s]\nTotal safe images: 1 out of 1",
"metrics": {
"predict_time": 7.5195654990000005,
"total_time": 7.62475
},
"output": [
"https://replicate.delivery/xezq/UsL9GcIVS1r8CRWoPADAW5YQSPzyOtPkLO41RLQfcHNbh9DKA/out-0.jpg"
],
"started_at": "2025-01-23T08:32:47.018185Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-j7wag4a64jmvngi2mgb3sqrpz3gzz3zn77rdzyydch7mf5qsu43q",
"get": "https://api.replicate.com/v1/predictions/pr0ewnev85rme0cmj95at7xwmm",
"cancel": "https://api.replicate.com/v1/predictions/pr0ewnev85rme0cmj95at7xwmm/cancel"
},
"version": "699912703d8dd9762877ff8d693a808a2e089bf74534fad1acb31e43b2e79f0b"
}
2025-01-23 08:32:47.403 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-23 08:32:47.404 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2778.88it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2650.84it/s]
2025-01-23 08:32:47.519 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s
free=29127590260736
Downloading weights
2025-01-23T08:32:47Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpj7glogp9/weights url=https://replicate.delivery/xezq/MKoZRVQ88p6dGhP6vUETXATQDGVufyleGAP9YnjkgfuXg1LoA/trained_model.tar
2025-01-23T08:32:49Z | INFO | [ Complete ] dest=/tmp/tmpj7glogp9/weights size="344 MB" total_elapsed=2.394s url=https://replicate.delivery/xezq/MKoZRVQ88p6dGhP6vUETXATQDGVufyleGAP9YnjkgfuXg1LoA/trained_model.tar
Downloaded weights in 2.42s
2025-01-23 08:32:49.939 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/67225bfb7e57db18
2025-01-23 08:32:50.052 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2025-01-23 08:32:50.053 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-23 08:32:50.053 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2779.57it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2651.48it/s]
2025-01-23 08:32:50.168 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s
Using seed: 21209
Image detected - setting to img2img mode
Input image size: 576x576
Input image size set to: 576x576
0it [00:00, ?it/s]
2it [00:00, 16.28it/s]
4it [00:00, 14.26it/s]
6it [00:00, 13.74it/s]
8it [00:00, 13.51it/s]
10it [00:00, 13.36it/s]
12it [00:00, 13.27it/s]
14it [00:01, 13.22it/s]
16it [00:01, 13.18it/s]
18it [00:01, 13.15it/s]
20it [00:01, 13.14it/s]
22it [00:01, 13.11it/s]
24it [00:01, 13.11it/s]
26it [00:01, 13.10it/s]
28it [00:02, 13.10it/s]
30it [00:02, 13.11it/s]
32it [00:02, 13.13it/s]
34it [00:02, 13.13it/s]
36it [00:02, 13.12it/s]
38it [00:02, 13.12it/s]
40it [00:03, 13.13it/s]
42it [00:03, 13.11it/s]
44it [00:03, 13.12it/s]
46it [00:03, 13.12it/s]
48it [00:03, 13.13it/s]
50it [00:03, 13.13it/s]
50it [00:03, 13.22it/s]
Total safe images: 1 out of 1
This model runs on Nvidia H100 GPU hardware. We don't yet have enough runs of this model to provide performance information.
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 runs on H100 hardware which costs $0.001525 per second. 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
2025-01-23 08:32:47.403 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-23 08:32:47.404 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2778.88it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2650.84it/s]
2025-01-23 08:32:47.519 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s
free=29127590260736
Downloading weights
2025-01-23T08:32:47Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpj7glogp9/weights url=https://replicate.delivery/xezq/MKoZRVQ88p6dGhP6vUETXATQDGVufyleGAP9YnjkgfuXg1LoA/trained_model.tar
2025-01-23T08:32:49Z | INFO | [ Complete ] dest=/tmp/tmpj7glogp9/weights size="344 MB" total_elapsed=2.394s url=https://replicate.delivery/xezq/MKoZRVQ88p6dGhP6vUETXATQDGVufyleGAP9YnjkgfuXg1LoA/trained_model.tar
Downloaded weights in 2.42s
2025-01-23 08:32:49.939 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/67225bfb7e57db18
2025-01-23 08:32:50.052 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2025-01-23 08:32:50.053 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-23 08:32:50.053 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2779.57it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2651.48it/s]
2025-01-23 08:32:50.168 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s
Using seed: 21209
Image detected - setting to img2img mode
Input image size: 576x576
Input image size set to: 576x576
0it [00:00, ?it/s]
2it [00:00, 16.28it/s]
4it [00:00, 14.26it/s]
6it [00:00, 13.74it/s]
8it [00:00, 13.51it/s]
10it [00:00, 13.36it/s]
12it [00:00, 13.27it/s]
14it [00:01, 13.22it/s]
16it [00:01, 13.18it/s]
18it [00:01, 13.15it/s]
20it [00:01, 13.14it/s]
22it [00:01, 13.11it/s]
24it [00:01, 13.11it/s]
26it [00:01, 13.10it/s]
28it [00:02, 13.10it/s]
30it [00:02, 13.11it/s]
32it [00:02, 13.13it/s]
34it [00:02, 13.13it/s]
36it [00:02, 13.12it/s]
38it [00:02, 13.12it/s]
40it [00:03, 13.13it/s]
42it [00:03, 13.11it/s]
44it [00:03, 13.12it/s]
46it [00:03, 13.12it/s]
48it [00:03, 13.13it/s]
50it [00:03, 13.13it/s]
50it [00:03, 13.22it/s]
Total safe images: 1 out of 1