Readme
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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";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run cloneofsimo/analog_diffusion_lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"cloneofsimo/analog_diffusion_lora:cfda4034a453627da6dd002d2ad959acb4c585b4e7204fed1d270eb3641fbea6",
{
input: {
width: 512,
height: 512,
prompt: "analog style closeup portrait of <1> cowboy hat",
lora_urls: "https://replicate.delivery/pbxt/IzbeguwVsW3PcC1gbiLy5SeALwk4sGgWroHagcYIn9I960bQA/tmpjlodd7vazekezip.safetensors",
scheduler: "DPMSolverMultistep",
lora_scales: "0.6",
num_outputs: 1,
adapter_type: "sketch",
guidance_scale: 6.5,
negative_prompt: "blur, haze",
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 cloneofsimo/analog_diffusion_lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"cloneofsimo/analog_diffusion_lora:cfda4034a453627da6dd002d2ad959acb4c585b4e7204fed1d270eb3641fbea6",
input={
"width": 512,
"height": 512,
"prompt": "analog style closeup portrait of <1> cowboy hat",
"lora_urls": "https://replicate.delivery/pbxt/IzbeguwVsW3PcC1gbiLy5SeALwk4sGgWroHagcYIn9I960bQA/tmpjlodd7vazekezip.safetensors",
"scheduler": "DPMSolverMultistep",
"lora_scales": "0.6",
"num_outputs": 1,
"adapter_type": "sketch",
"guidance_scale": 6.5,
"negative_prompt": "blur, haze",
"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 cloneofsimo/analog_diffusion_lora 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": "cloneofsimo/analog_diffusion_lora:cfda4034a453627da6dd002d2ad959acb4c585b4e7204fed1d270eb3641fbea6",
"input": {
"width": 512,
"height": 512,
"prompt": "analog style closeup portrait of <1> cowboy hat",
"lora_urls": "https://replicate.delivery/pbxt/IzbeguwVsW3PcC1gbiLy5SeALwk4sGgWroHagcYIn9I960bQA/tmpjlodd7vazekezip.safetensors",
"scheduler": "DPMSolverMultistep",
"lora_scales": "0.6",
"num_outputs": 1,
"adapter_type": "sketch",
"guidance_scale": 6.5,
"negative_prompt": "blur, haze",
"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": "2023-03-01T16:54:23.542761Z",
"created_at": "2023-03-01T16:54:12.115799Z",
"data_removed": false,
"error": null,
"id": "jgow3glngvexlpucx6zy6tunsa",
"input": {
"width": 512,
"height": 512,
"prompt": "analog style closeup portrait of <1> cowboy hat",
"lora_urls": "https://replicate.delivery/pbxt/IzbeguwVsW3PcC1gbiLy5SeALwk4sGgWroHagcYIn9I960bQA/tmpjlodd7vazekezip.safetensors",
"scheduler": "DPMSolverMultistep",
"lora_scales": "0.6",
"num_outputs": 1,
"adapter_type": "sketch",
"guidance_scale": "6.5",
"negative_prompt": "blur, haze",
"prompt_strength": 0.8,
"num_inference_steps": 50
},
"logs": "Using seed: 16285\nGenerating image of 512 x 512 with prompt: analog style closeup portrait of <1> cowboy hat\nThe requested LoRAs are loaded.\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:12, 3.94it/s]\n 4%|▍ | 2/50 [00:00<00:10, 4.41it/s]\n 6%|▌ | 3/50 [00:00<00:10, 4.65it/s]\n 8%|▊ | 4/50 [00:00<00:09, 4.78it/s]\n 10%|█ | 5/50 [00:01<00:09, 4.85it/s]\n 12%|█▏ | 6/50 [00:01<00:09, 4.86it/s]\n 14%|█▍ | 7/50 [00:01<00:08, 4.88it/s]\n 16%|█▌ | 8/50 [00:01<00:08, 4.90it/s]\n 18%|█▊ | 9/50 [00:01<00:08, 4.92it/s]\n 20%|██ | 10/50 [00:02<00:08, 4.93it/s]\n 22%|██▏ | 11/50 [00:02<00:07, 4.93it/s]\n 24%|██▍ | 12/50 [00:02<00:07, 4.94it/s]\n 26%|██▌ | 13/50 [00:02<00:07, 4.93it/s]\n 28%|██▊ | 14/50 [00:02<00:07, 4.94it/s]\n 30%|███ | 15/50 [00:03<00:07, 4.95it/s]\n 32%|███▏ | 16/50 [00:03<00:06, 4.95it/s]\n 34%|███▍ | 17/50 [00:03<00:06, 4.94it/s]\n 36%|███▌ | 18/50 [00:03<00:06, 4.93it/s]\n 38%|███▊ | 19/50 [00:03<00:06, 4.94it/s]\n 40%|████ | 20/50 [00:04<00:06, 4.95it/s]\n 42%|████▏ | 21/50 [00:04<00:05, 4.94it/s]\n 44%|████▍ | 22/50 [00:04<00:05, 4.94it/s]\n 46%|████▌ | 23/50 [00:04<00:05, 4.93it/s]\n 48%|████▊ | 24/50 [00:04<00:05, 4.94it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.93it/s]\n 52%|█████▏ | 26/50 [00:05<00:04, 4.93it/s]\n 54%|█████▍ | 27/50 [00:05<00:04, 4.93it/s]\n 56%|█████▌ | 28/50 [00:05<00:04, 4.92it/s]\n 58%|█████▊ | 29/50 [00:05<00:04, 4.92it/s]\n 60%|██████ | 30/50 [00:06<00:04, 4.92it/s]\n 62%|██████▏ | 31/50 [00:06<00:03, 4.92it/s]\n 64%|██████▍ | 32/50 [00:06<00:03, 4.91it/s]\n 66%|██████▌ | 33/50 [00:06<00:03, 4.91it/s]\n 68%|██████▊ | 34/50 [00:06<00:03, 4.89it/s]\n 70%|███████ | 35/50 [00:07<00:03, 4.88it/s]\n 72%|███████▏ | 36/50 [00:07<00:02, 4.86it/s]\n 74%|███████▍ | 37/50 [00:07<00:02, 4.88it/s]\n 76%|███████▌ | 38/50 [00:07<00:02, 4.89it/s]\n 78%|███████▊ | 39/50 [00:07<00:02, 4.89it/s]\n 80%|████████ | 40/50 [00:08<00:02, 4.90it/s]\n 82%|████████▏ | 41/50 [00:08<00:01, 4.90it/s]\n 84%|████████▍ | 42/50 [00:08<00:01, 4.90it/s]\n 86%|████████▌ | 43/50 [00:08<00:01, 4.89it/s]\n 88%|████████▊ | 44/50 [00:08<00:01, 4.89it/s]\n 90%|█████████ | 45/50 [00:09<00:01, 4.87it/s]\n 92%|█████████▏| 46/50 [00:09<00:00, 4.85it/s]\n 94%|█████████▍| 47/50 [00:09<00:00, 4.87it/s]\n 96%|█████████▌| 48/50 [00:09<00:00, 4.87it/s]\n 98%|█████████▊| 49/50 [00:10<00:00, 4.88it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.86it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.89it/s]",
"metrics": {
"predict_time": 11.342725,
"total_time": 11.426962
},
"output": [
"https://replicate.delivery/pbxt/entxiWe9NlvZ9Ea8OayJ4vgBDjGEccav699HzP9hrlqepmGhA/out-0.png"
],
"started_at": "2023-03-01T16:54:12.200036Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/jgow3glngvexlpucx6zy6tunsa",
"cancel": "https://api.replicate.com/v1/predictions/jgow3glngvexlpucx6zy6tunsa/cancel"
},
"version": "b71669eeda89a08ce8294c3e79fa203417918161b961c6de3215fce20ff9bc87"
}
Using seed: 16285
Generating image of 512 x 512 with prompt: analog style closeup portrait of <1> cowboy hat
The requested LoRAs are loaded.
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This output was created using a different version of the model, cloneofsimo/analog_diffusion_lora:b71669ee.
This model costs approximately $0.0027 to run on Replicate, or 370 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 T4 GPU hardware. Predictions typically complete within 12 seconds.
This model doesn't have a readme.
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.
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: 16285
Generating image of 512 x 512 with prompt: analog style closeup portrait of <1> cowboy hat
The requested LoRAs are loaded.
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