Readme
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'''Last update: Now supports img2img.''' SDXL Canny controlnet with LoRA support. (Updated 1 year, 4 months ago)
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 fermatresearch/sdxl-controlnet-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"fermatresearch/sdxl-controlnet-lora:3bb13fe1c33c35987b33792b01b71ed6529d03f165d1c2416375859f09ca9fef",
{
input: {
seed: null,
image: "https://replicate.delivery/pbxt/JiOTMCHj4oGrTTf8Pg2r7vyI8YdXc5jL2IDyC2SfhuggjYe6/out-0%20%281%29.png",
prompt: "shot in the style of sksfer, a woman in alaska",
refine: "base_image_refiner",
strength: 0.8,
scheduler: "K_EULER",
lora_scale: 0.95,
num_outputs: 1,
lora_weights: "https://pbxt.replicate.delivery/mwN3AFyYZyouOB03Uhw8ubKW9rpqMgdtL9zYV9GF2WGDiwbE/trained_model.tar",
refine_steps: 20,
guidance_scale: 7.5,
apply_watermark: true,
condition_scale: 0.5,
negative_prompt: "",
num_inference_steps: 40
}
}
);
// 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 fermatresearch/sdxl-controlnet-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"fermatresearch/sdxl-controlnet-lora:3bb13fe1c33c35987b33792b01b71ed6529d03f165d1c2416375859f09ca9fef",
input={
"seed": null,
"image": "https://replicate.delivery/pbxt/JiOTMCHj4oGrTTf8Pg2r7vyI8YdXc5jL2IDyC2SfhuggjYe6/out-0%20%281%29.png",
"prompt": "shot in the style of sksfer, a woman in alaska",
"refine": "base_image_refiner",
"strength": 0.8,
"scheduler": "K_EULER",
"lora_scale": 0.95,
"num_outputs": 1,
"lora_weights": "https://pbxt.replicate.delivery/mwN3AFyYZyouOB03Uhw8ubKW9rpqMgdtL9zYV9GF2WGDiwbE/trained_model.tar",
"refine_steps": 20,
"guidance_scale": 7.5,
"apply_watermark": True,
"condition_scale": 0.5,
"negative_prompt": "",
"num_inference_steps": 40
}
)
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 fermatresearch/sdxl-controlnet-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": "fermatresearch/sdxl-controlnet-lora:3bb13fe1c33c35987b33792b01b71ed6529d03f165d1c2416375859f09ca9fef",
"input": {
"seed": null,
"image": "https://replicate.delivery/pbxt/JiOTMCHj4oGrTTf8Pg2r7vyI8YdXc5jL2IDyC2SfhuggjYe6/out-0%20%281%29.png",
"prompt": "shot in the style of sksfer, a woman in alaska",
"refine": "base_image_refiner",
"strength": 0.8,
"scheduler": "K_EULER",
"lora_scale": 0.95,
"num_outputs": 1,
"lora_weights": "https://pbxt.replicate.delivery/mwN3AFyYZyouOB03Uhw8ubKW9rpqMgdtL9zYV9GF2WGDiwbE/trained_model.tar",
"refine_steps": 20,
"guidance_scale": 7.5,
"apply_watermark": true,
"condition_scale": 0.5,
"negative_prompt": "",
"num_inference_steps": 40
}
}' \
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/fermatresearch/sdxl-controlnet-lora@sha256:3bb13fe1c33c35987b33792b01b71ed6529d03f165d1c2416375859f09ca9fef \
-i 'seed=null' \
-i 'image="https://replicate.delivery/pbxt/JiOTMCHj4oGrTTf8Pg2r7vyI8YdXc5jL2IDyC2SfhuggjYe6/out-0%20%281%29.png"' \
-i 'prompt="shot in the style of sksfer, a woman in alaska"' \
-i 'refine="base_image_refiner"' \
-i 'strength=0.8' \
-i 'scheduler="K_EULER"' \
-i 'lora_scale=0.95' \
-i 'num_outputs=1' \
-i 'lora_weights="https://pbxt.replicate.delivery/mwN3AFyYZyouOB03Uhw8ubKW9rpqMgdtL9zYV9GF2WGDiwbE/trained_model.tar"' \
-i 'refine_steps=20' \
-i 'guidance_scale=7.5' \
-i 'apply_watermark=true' \
-i 'condition_scale=0.5' \
-i 'negative_prompt=""' \
-i 'num_inference_steps=40'
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/fermatresearch/sdxl-controlnet-lora@sha256:3bb13fe1c33c35987b33792b01b71ed6529d03f165d1c2416375859f09ca9fef
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "seed": null, "image": "https://replicate.delivery/pbxt/JiOTMCHj4oGrTTf8Pg2r7vyI8YdXc5jL2IDyC2SfhuggjYe6/out-0%20%281%29.png", "prompt": "shot in the style of sksfer, a woman in alaska", "refine": "base_image_refiner", "strength": 0.8, "scheduler": "K_EULER", "lora_scale": 0.95, "num_outputs": 1, "lora_weights": "https://pbxt.replicate.delivery/mwN3AFyYZyouOB03Uhw8ubKW9rpqMgdtL9zYV9GF2WGDiwbE/trained_model.tar", "refine_steps": 20, "guidance_scale": 7.5, "apply_watermark": true, "condition_scale": 0.5, "negative_prompt": "", "num_inference_steps": 40 } }' \ 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 $0.043. Alternatively, try out our featured models for free.
By signing in, you agree to our
terms of service and privacy policy
{
"completed_at": "2023-10-17T13:48:50.759475Z",
"created_at": "2023-10-17T13:48:30.378425Z",
"data_removed": false,
"error": null,
"id": "ruzsnmtb7idrwecy2ue5ig6gli",
"input": {
"seed": null,
"image": "https://replicate.delivery/pbxt/JiOTMCHj4oGrTTf8Pg2r7vyI8YdXc5jL2IDyC2SfhuggjYe6/out-0%20%281%29.png",
"prompt": "shot in the style of sksfer, a woman in alaska",
"refine": "base_image_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.95,
"num_outputs": 1,
"lora_weights": "https://pbxt.replicate.delivery/mwN3AFyYZyouOB03Uhw8ubKW9rpqMgdtL9zYV9GF2WGDiwbE/trained_model.tar",
"refine_steps": 20,
"guidance_scale": 7.5,
"apply_watermark": true,
"condition_scale": 0.5,
"negative_prompt": "",
"num_inference_steps": 40
},
"logs": "Using seed: 44186\nloading custom weights\nweights already in cache\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: shot in the style of <s0><s1>, a woman in alaska\nOriginal width:1024, height:1024\nAspect Ratio: 1.00\nnew_width:1024, new_height:1024\ntxt2img mode\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:14, 2.72it/s]\n 5%|▌ | 2/40 [00:00<00:13, 2.73it/s]\n 8%|▊ | 3/40 [00:01<00:13, 2.73it/s]\n 10%|█ | 4/40 [00:01<00:13, 2.73it/s]\n 12%|█▎ | 5/40 [00:01<00:12, 2.73it/s]\n 15%|█▌ | 6/40 [00:02<00:12, 2.73it/s]\n 18%|█▊ | 7/40 [00:02<00:12, 2.73it/s]\n 20%|██ | 8/40 [00:02<00:11, 2.73it/s]\n 22%|██▎ | 9/40 [00:03<00:11, 2.73it/s]\n 25%|██▌ | 10/40 [00:03<00:11, 2.72it/s]\n 28%|██▊ | 11/40 [00:04<00:10, 2.72it/s]\n 30%|███ | 12/40 [00:04<00:10, 2.72it/s]\n 32%|███▎ | 13/40 [00:04<00:09, 2.72it/s]\n 35%|███▌ | 14/40 [00:05<00:09, 2.72it/s]\n 38%|███▊ | 15/40 [00:05<00:09, 2.72it/s]\n 40%|████ | 16/40 [00:05<00:08, 2.72it/s]\n 42%|████▎ | 17/40 [00:06<00:08, 2.71it/s]\n 45%|████▌ | 18/40 [00:06<00:08, 2.71it/s]\n 48%|████▊ | 19/40 [00:06<00:07, 2.71it/s]\n 50%|█████ | 20/40 [00:07<00:07, 2.71it/s]\n 52%|█████▎ | 21/40 [00:07<00:06, 2.71it/s]\n 55%|█████▌ | 22/40 [00:08<00:06, 2.72it/s]\n 57%|█████▊ | 23/40 [00:08<00:06, 2.71it/s]\n 60%|██████ | 24/40 [00:08<00:05, 2.71it/s]\n 62%|██████▎ | 25/40 [00:09<00:05, 2.71it/s]\n 65%|██████▌ | 26/40 [00:09<00:05, 2.71it/s]\n 68%|██████▊ | 27/40 [00:09<00:04, 2.71it/s]\n 70%|███████ | 28/40 [00:10<00:04, 2.72it/s]\n 72%|███████▎ | 29/40 [00:10<00:04, 2.71it/s]\n 75%|███████▌ | 30/40 [00:11<00:03, 2.71it/s]\n 78%|███████▊ | 31/40 [00:11<00:03, 2.71it/s]\n 80%|████████ | 32/40 [00:11<00:02, 2.71it/s]\n 82%|████████▎ | 33/40 [00:12<00:02, 2.71it/s]\n 85%|████████▌ | 34/40 [00:12<00:02, 2.71it/s]\n 88%|████████▊ | 35/40 [00:12<00:01, 2.71it/s]\n 90%|█████████ | 36/40 [00:13<00:01, 2.71it/s]\n 92%|█████████▎| 37/40 [00:13<00:01, 2.71it/s]\n 95%|█████████▌| 38/40 [00:13<00:00, 2.71it/s]\n 98%|█████████▊| 39/40 [00:14<00:00, 2.71it/s]\n100%|██████████| 40/40 [00:14<00:00, 2.71it/s]\n100%|██████████| 40/40 [00:14<00:00, 2.72it/s]\n 0%| | 0/6 [00:00<?, ?it/s]\n 17%|█▋ | 1/6 [00:00<00:01, 4.32it/s]\n 33%|███▎ | 2/6 [00:00<00:00, 4.30it/s]\n 50%|█████ | 3/6 [00:00<00:00, 4.30it/s]\n 67%|██████▋ | 4/6 [00:00<00:00, 4.28it/s]\n 83%|████████▎ | 5/6 [00:01<00:00, 4.28it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.28it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.29it/s]",
"metrics": {
"predict_time": 20.411215,
"total_time": 20.38105
},
"output": [
"https://replicate.delivery/pbxt/oDtYIK2lDoaKMtdE4E5ozQSa61BU3gc4aRvGF3xmFpdwCxbE/out-0.png"
],
"started_at": "2023-10-17T13:48:30.348260Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/ruzsnmtb7idrwecy2ue5ig6gli",
"cancel": "https://api.replicate.com/v1/predictions/ruzsnmtb7idrwecy2ue5ig6gli/cancel"
},
"version": "a4fb84022361602a2401d74435229e90da63ea4a2aab40ebf79afd7af5a081d4"
}
Using seed: 44186
loading custom weights
weights already in cache
Loading fine-tuned model
Does not have Unet. assume we are using LoRA
Loading Unet LoRA
Prompt: shot in the style of <s0><s1>, a woman in alaska
Original width:1024, height:1024
Aspect Ratio: 1.00
new_width:1024, new_height:1024
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This output was created using a different version of the model, fermatresearch/sdxl-controlnet-lora:a4fb8402.
This model costs approximately $0.043 to run on Replicate, or 23 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 45 seconds. The predict time for this model varies significantly based on the inputs.
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 $0.043 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
Using seed: 44186
loading custom weights
weights already in cache
Loading fine-tuned model
Does not have Unet. assume we are using LoRA
Loading Unet LoRA
Prompt: shot in the style of <s0><s1>, a woman in alaska
Original width:1024, height:1024
Aspect Ratio: 1.00
new_width:1024, new_height:1024
txt2img mode
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