Readme
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Flux Lora inspired by Kodak Portra 800
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 shapestudio/portra-800-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"shapestudio/portra-800-flux:3d616c81c96b5578e485988d51f260c4159b8ce7822cf13fa0af63a7e5c833c2",
{
input: {
model: "dev",
prompt: "A cup of coffee where the steam forms a cloud, raining tiny droplets back into the cup, in a self-sustaining cycle.",
go_fast: false,
lora_scale: 0.86,
megapixels: "1",
num_outputs: 1,
aspect_ratio: "1:1",
output_format: "webp",
guidance_scale: 3.5,
output_quality: 80,
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 shapestudio/portra-800-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"shapestudio/portra-800-flux:3d616c81c96b5578e485988d51f260c4159b8ce7822cf13fa0af63a7e5c833c2",
input={
"model": "dev",
"prompt": "A cup of coffee where the steam forms a cloud, raining tiny droplets back into the cup, in a self-sustaining cycle.",
"go_fast": False,
"lora_scale": 0.86,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"output_quality": 80,
"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 shapestudio/portra-800-flux 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": "shapestudio/portra-800-flux:3d616c81c96b5578e485988d51f260c4159b8ce7822cf13fa0af63a7e5c833c2",
"input": {
"model": "dev",
"prompt": "A cup of coffee where the steam forms a cloud, raining tiny droplets back into the cup, in a self-sustaining cycle.",
"go_fast": false,
"lora_scale": 0.86,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"output_quality": 80,
"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": "2024-08-20T12:54:55.535380Z",
"created_at": "2024-08-20T12:54:23.618000Z",
"data_removed": false,
"error": null,
"id": "ngtcenjeg9rm20chdzdaa0qwwr",
"input": {
"model": "dev",
"prompt": "A cup of coffee where the steam forms a cloud, raining tiny droplets back into the cup, in a self-sustaining cycle.",
"lora_scale": 0.86,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"output_quality": 80,
"num_inference_steps": 38
},
"logs": "Using seed: 18640\nPrompt: A cup of coffee where the steam forms a cloud, raining tiny droplets back into the cup, in a self-sustaining cycle.\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/38 [00:00<?, ?it/s]\n 3%|▎ | 1/38 [00:00<00:10, 3.52it/s]\n 5%|▌ | 2/38 [00:00<00:09, 3.90it/s]\n 8%|▊ | 3/38 [00:00<00:09, 3.70it/s]\n 11%|█ | 4/38 [00:01<00:09, 3.62it/s]\n 13%|█▎ | 5/38 [00:01<00:09, 3.58it/s]\n 16%|█▌ | 6/38 [00:01<00:09, 3.55it/s]\n 18%|█▊ | 7/38 [00:01<00:08, 3.53it/s]\n 21%|██ | 8/38 [00:02<00:08, 3.53it/s]\n 24%|██▎ | 9/38 [00:02<00:08, 3.53it/s]\n 26%|██▋ | 10/38 [00:02<00:07, 3.52it/s]\n 29%|██▉ | 11/38 [00:03<00:07, 3.51it/s]\n 32%|███▏ | 12/38 [00:03<00:07, 3.51it/s]\n 34%|███▍ | 13/38 [00:03<00:07, 3.52it/s]\n 37%|███▋ | 14/38 [00:03<00:06, 3.51it/s]\n 39%|███▉ | 15/38 [00:04<00:06, 3.51it/s]\n 42%|████▏ | 16/38 [00:04<00:06, 3.51it/s]\n 45%|████▍ | 17/38 [00:04<00:05, 3.51it/s]\n 47%|████▋ | 18/38 [00:05<00:05, 3.51it/s]\n 50%|█████ | 19/38 [00:05<00:05, 3.50it/s]\n 53%|█████▎ | 20/38 [00:05<00:05, 3.51it/s]\n 55%|█████▌ | 21/38 [00:05<00:04, 3.51it/s]\n 58%|█████▊ | 22/38 [00:06<00:04, 3.51it/s]\n 61%|██████ | 23/38 [00:06<00:04, 3.50it/s]\n 63%|██████▎ | 24/38 [00:06<00:03, 3.51it/s]\n 66%|██████▌ | 25/38 [00:07<00:03, 3.51it/s]\n 68%|██████▊ | 26/38 [00:07<00:03, 3.51it/s]\n 71%|███████ | 27/38 [00:07<00:03, 3.50it/s]\n 74%|███████▎ | 28/38 [00:07<00:02, 3.50it/s]\n 76%|███████▋ | 29/38 [00:08<00:02, 3.51it/s]\n 79%|███████▉ | 30/38 [00:08<00:02, 3.51it/s]\n 82%|████████▏ | 31/38 [00:08<00:01, 3.51it/s]\n 84%|████████▍ | 32/38 [00:09<00:01, 3.51it/s]\n 87%|████████▋ | 33/38 [00:09<00:01, 3.51it/s]\n 89%|████████▉ | 34/38 [00:09<00:01, 3.51it/s]\n 92%|█████████▏| 35/38 [00:09<00:00, 3.51it/s]\n 95%|█████████▍| 36/38 [00:10<00:00, 3.51it/s]\n 97%|█████████▋| 37/38 [00:10<00:00, 3.51it/s]\n100%|██████████| 38/38 [00:10<00:00, 3.51it/s]\n100%|██████████| 38/38 [00:10<00:00, 3.52it/s]",
"metrics": {
"predict_time": 19.338690129,
"total_time": 31.91738
},
"output": [
"https://replicate.delivery/yhqm/9M0L6kvWqfQ5YKhsVivNhpIia4F9ajrOjuOARbD1oc5PISqJA/out-0.webp"
],
"started_at": "2024-08-20T12:54:36.196689Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/ngtcenjeg9rm20chdzdaa0qwwr",
"cancel": "https://api.replicate.com/v1/predictions/ngtcenjeg9rm20chdzdaa0qwwr/cancel"
},
"version": "3d616c81c96b5578e485988d51f260c4159b8ce7822cf13fa0af63a7e5c833c2"
}
Using seed: 18640
Prompt: A cup of coffee where the steam forms a cloud, raining tiny droplets back into the cup, in a self-sustaining cycle.
txt2img mode
Using dev model
Loading LoRA weights
LoRA weights loaded successfully
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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
Using seed: 18640
Prompt: A cup of coffee where the steam forms a cloud, raining tiny droplets back into the cup, in a self-sustaining cycle.
txt2img mode
Using dev model
Loading LoRA weights
LoRA weights loaded successfully
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