Readme
Inference optimized with Lightning 8steps, Stable Fast, and dynamic quantized int8
Photomaker V1 optimized with Lightning 8steps
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 kelvincai522/photomaker-v1-lightning using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"kelvincai522/photomaker-v1-lightning:bea9c27a8620bda18eab53bce5b65afe3fabdb55e15316d90d0c38b0f41e1f9c",
{
input: {
prompt: "score_9 score_8_up score_7_up anime img 1girl masterpiece very_aesthetic hi_res absurd_res superabsurd_res",
num_steps: 16,
style_name: "(No style)",
input_image: "https://replicate.delivery/pbxt/KFRc9kyW6lLALePRbphzLaZnMyqjYUH8Tles73OvOVfXUcj8/yangmi_1.jpg",
num_outputs: 1,
guidance_scale: 5,
negative_prompt: "score_1 score_2 score_3 worst_quality bad_quality jpeg_artifacts source_cartoon 3d censor+ monochrome blurry lowres watermark text low_res oversaturated crappy_art low_quality blurry bad_anatomy extra_digits fewer_digits simple_background very_displeasing watermark signature",
style_strength_ratio: 15
}
}
);
// 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 kelvincai522/photomaker-v1-lightning using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"kelvincai522/photomaker-v1-lightning:bea9c27a8620bda18eab53bce5b65afe3fabdb55e15316d90d0c38b0f41e1f9c",
input={
"prompt": "score_9 score_8_up score_7_up anime img 1girl masterpiece very_aesthetic hi_res absurd_res superabsurd_res",
"num_steps": 16,
"style_name": "(No style)",
"input_image": "https://replicate.delivery/pbxt/KFRc9kyW6lLALePRbphzLaZnMyqjYUH8Tles73OvOVfXUcj8/yangmi_1.jpg",
"num_outputs": 1,
"guidance_scale": 5,
"negative_prompt": "score_1 score_2 score_3 worst_quality bad_quality jpeg_artifacts source_cartoon 3d censor+ monochrome blurry lowres watermark text low_res oversaturated crappy_art low_quality blurry bad_anatomy extra_digits fewer_digits simple_background very_displeasing watermark signature",
"style_strength_ratio": 15
}
)
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 kelvincai522/photomaker-v1-lightning 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": "kelvincai522/photomaker-v1-lightning:bea9c27a8620bda18eab53bce5b65afe3fabdb55e15316d90d0c38b0f41e1f9c",
"input": {
"prompt": "score_9 score_8_up score_7_up anime img 1girl masterpiece very_aesthetic hi_res absurd_res superabsurd_res",
"num_steps": 16,
"style_name": "(No style)",
"input_image": "https://replicate.delivery/pbxt/KFRc9kyW6lLALePRbphzLaZnMyqjYUH8Tles73OvOVfXUcj8/yangmi_1.jpg",
"num_outputs": 1,
"guidance_scale": 5,
"negative_prompt": "score_1 score_2 score_3 worst_quality bad_quality jpeg_artifacts source_cartoon 3d censor+ monochrome blurry lowres watermark text low_res oversaturated crappy_art low_quality blurry bad_anatomy extra_digits fewer_digits simple_background very_displeasing watermark signature",
"style_strength_ratio": 15
}
}' \
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/kelvincai522/photomaker-v1-lightning@sha256:bea9c27a8620bda18eab53bce5b65afe3fabdb55e15316d90d0c38b0f41e1f9c \
-i 'prompt="score_9 score_8_up score_7_up anime img 1girl masterpiece very_aesthetic hi_res absurd_res superabsurd_res"' \
-i 'num_steps=16' \
-i 'style_name="(No style)"' \
-i 'input_image="https://replicate.delivery/pbxt/KFRc9kyW6lLALePRbphzLaZnMyqjYUH8Tles73OvOVfXUcj8/yangmi_1.jpg"' \
-i 'num_outputs=1' \
-i 'guidance_scale=5' \
-i 'negative_prompt="score_1 score_2 score_3 worst_quality bad_quality jpeg_artifacts source_cartoon 3d censor+ monochrome blurry lowres watermark text low_res oversaturated crappy_art low_quality blurry bad_anatomy extra_digits fewer_digits simple_background very_displeasing watermark signature"' \
-i 'style_strength_ratio=15'
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/kelvincai522/photomaker-v1-lightning@sha256:bea9c27a8620bda18eab53bce5b65afe3fabdb55e15316d90d0c38b0f41e1f9c
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "prompt": "score_9 score_8_up score_7_up anime img 1girl masterpiece very_aesthetic hi_res absurd_res superabsurd_res", "num_steps": 16, "style_name": "(No style)", "input_image": "https://replicate.delivery/pbxt/KFRc9kyW6lLALePRbphzLaZnMyqjYUH8Tles73OvOVfXUcj8/yangmi_1.jpg", "num_outputs": 1, "guidance_scale": 5, "negative_prompt": "score_1 score_2 score_3 worst_quality bad_quality jpeg_artifacts source_cartoon 3d censor+ monochrome blurry lowres watermark text low_res oversaturated crappy_art low_quality blurry bad_anatomy extra_digits fewer_digits simple_background very_displeasing watermark signature", "style_strength_ratio": 15 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
Each run costs approximately $0.18. Alternatively, try out our featured models for free.
By signing in, you agree to our
terms of service and privacy policy
{
"completed_at": "2025-03-11T16:35:20.157063Z",
"created_at": "2025-03-11T16:33:52.916000Z",
"data_removed": false,
"error": null,
"id": "t0t381hn2hrme0cngr78e8k5kr",
"input": {
"prompt": "score_9 score_8_up score_7_up anime img 1girl masterpiece very_aesthetic hi_res absurd_res superabsurd_res",
"num_steps": 16,
"style_name": "(No style)",
"input_image": "https://replicate.delivery/pbxt/KFRc9kyW6lLALePRbphzLaZnMyqjYUH8Tles73OvOVfXUcj8/yangmi_1.jpg",
"num_outputs": 1,
"guidance_scale": 5,
"negative_prompt": "score_1 score_2 score_3 worst_quality bad_quality jpeg_artifacts source_cartoon 3d censor+ monochrome blurry lowres watermark text low_res oversaturated crappy_art low_quality blurry bad_anatomy extra_digits fewer_digits simple_background very_displeasing watermark signature",
"style_strength_ratio": 15
},
"logs": "Using seed 720498486...\nLoading image /tmp/tmpcgshv8a6yangmi_1.jpg...\nSetting seed...\nStart inference...\n[Debug] Prompt: score_9 score_8_up score_7_up anime img 1girl masterpiece very_aesthetic hi_res absurd_res superabsurd_res\n[Debug] Neg Prompt: score_1 score_2 score_3 worst_quality bad_quality jpeg_artifacts source_cartoon 3d censor+ monochrome blurry lowres watermark text low_res oversaturated crappy_art low_quality blurry bad_anatomy extra_digits fewer_digits simple_background very_displeasing watermark signature\nStart merge step: 2\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/torch/cuda/graphs.py:88: UserWarning: The CUDA Graph is empty. This usually means that the graph was attempted to be captured on wrong device or stream. (Triggered internally at ../aten/src/ATen/cuda/CUDAGraph.cpp:224.)\nsuper().capture_end()\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!\nreturn func(*args, **kwargs)\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python list might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!\nreturn func(*args, **kwargs)\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!\nreturn func(*args, **kwargs)\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.\nreturn func(*args, **kwargs)\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/utils/flat_tensors.py:275: TracerWarning: torch.Tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.\nreturn super().__new__(cls, x, *args, **kwargs)\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: torch.as_tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.\nreturn func(*args, **kwargs)\n 0%| | 0/16 [00:00<?, ?it/s]\n 6%|▋ | 1/16 [00:37<09:17, 37.14s/it]\n 12%|█▎ | 2/16 [00:37<03:35, 15.36s/it]\n 19%|█▉ | 3/16 [00:37<01:49, 8.40s/it]\n 25%|██▌ | 4/16 [00:37<01:01, 5.13s/it]\n 31%|███▏ | 5/16 [00:37<00:36, 3.32s/it]\n 38%|███▊ | 6/16 [00:37<00:22, 2.23s/it]\n 44%|████▍ | 7/16 [00:37<00:13, 1.54s/it]\n 50%|█████ | 8/16 [00:37<00:08, 1.08s/it]\n 56%|█████▋ | 9/16 [00:38<00:05, 1.28it/s]\n 62%|██████▎ | 10/16 [00:38<00:03, 1.74it/s]\n 69%|██████▉ | 11/16 [00:38<00:02, 2.31it/s]\n 75%|███████▌ | 12/16 [00:38<00:01, 2.98it/s]\n 81%|████████▏ | 13/16 [00:38<00:00, 3.73it/s]\n 88%|████████▊ | 14/16 [00:38<00:00, 4.52it/s]\n 94%|█████████▍| 15/16 [00:38<00:00, 5.30it/s]\n100%|██████████| 16/16 [00:38<00:00, 6.03it/s]\n100%|██████████| 16/16 [00:38<00:00, 2.43s/it]\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!\nreturn func(*args, **kwargs)\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.\nreturn func(*args, **kwargs)\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!\nreturn func(*args, **kwargs)\nSaving images to file...",
"metrics": {
"predict_time": 44.680676421,
"total_time": 87.241063
},
"output": [
"https://replicate.delivery/xezq/uDVA1ZOboezfPkTPC0Jzm1qryLH3M0vQf4oNrPjyRVAQCDvoA/image_0.png"
],
"started_at": "2025-03-11T16:34:35.476387Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-6hqimduvbnuhgodpv7usqnul4ea222tuhktltacxmtqm6h45wxxq",
"get": "https://api.replicate.com/v1/predictions/t0t381hn2hrme0cngr78e8k5kr",
"cancel": "https://api.replicate.com/v1/predictions/t0t381hn2hrme0cngr78e8k5kr/cancel"
},
"version": "0ccd19c5e076ebf0d6448522d5d7113f81057ed725c153713b394a1d26663b31"
}
Using seed 720498486...
Loading image /tmp/tmpcgshv8a6yangmi_1.jpg...
Setting seed...
Start inference...
[Debug] Prompt: score_9 score_8_up score_7_up anime img 1girl masterpiece very_aesthetic hi_res absurd_res superabsurd_res
[Debug] Neg Prompt: score_1 score_2 score_3 worst_quality bad_quality jpeg_artifacts source_cartoon 3d censor+ monochrome blurry lowres watermark text low_res oversaturated crappy_art low_quality blurry bad_anatomy extra_digits fewer_digits simple_background very_displeasing watermark signature
Start merge step: 2
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/torch/cuda/graphs.py:88: UserWarning: The CUDA Graph is empty. This usually means that the graph was attempted to be captured on wrong device or stream. (Triggered internally at ../aten/src/ATen/cuda/CUDAGraph.cpp:224.)
super().capture_end()
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
return func(*args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python list might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
return func(*args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
return func(*args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
return func(*args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/utils/flat_tensors.py:275: TracerWarning: torch.Tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
return super().__new__(cls, x, *args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: torch.as_tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
return func(*args, **kwargs)
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/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
return func(*args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
return func(*args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
return func(*args, **kwargs)
Saving images to file...
This output was created using a different version of the model, kelvincai522/photomaker-v1-lightning:0ccd19c5.
This model costs approximately $0.18 to run on Replicate, or 5 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 4 minutes.
Inference optimized with Lightning 8steps, Stable Fast, and dynamic quantized int8
This model is cold. 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 $0.18 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
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 720498486...
Loading image /tmp/tmpcgshv8a6yangmi_1.jpg...
Setting seed...
Start inference...
[Debug] Prompt: score_9 score_8_up score_7_up anime img 1girl masterpiece very_aesthetic hi_res absurd_res superabsurd_res
[Debug] Neg Prompt: score_1 score_2 score_3 worst_quality bad_quality jpeg_artifacts source_cartoon 3d censor+ monochrome blurry lowres watermark text low_res oversaturated crappy_art low_quality blurry bad_anatomy extra_digits fewer_digits simple_background very_displeasing watermark signature
Start merge step: 2
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/torch/cuda/graphs.py:88: UserWarning: The CUDA Graph is empty. This usually means that the graph was attempted to be captured on wrong device or stream. (Triggered internally at ../aten/src/ATen/cuda/CUDAGraph.cpp:224.)
super().capture_end()
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
return func(*args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python list might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
return func(*args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
return func(*args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
return func(*args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/utils/flat_tensors.py:275: TracerWarning: torch.Tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
return super().__new__(cls, x, *args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: torch.as_tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
return func(*args, **kwargs)
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/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python number might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
return func(*args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
return func(*args, **kwargs)
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/sfast/jit/overrides.py:21: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
return func(*args, **kwargs)
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