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alexgenovese /sdxl-custom-model:a08504bd
This version has been disabled because it consistently fails to complete setup.
Input
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variableexport 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 alexgenovese/sdxl-custom-model using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"alexgenovese/sdxl-custom-model:a08504bd6b123bb993f648c6361041a3cc3f721a24ab6a1619b10f03dd8c0dff",
{
input: {
width: 1024,
height: 1024,
prompt: "a full body realistic photo of beautiful woman 40 y.o, walking in Madison Square Garden, smile, blue eyes, short hair, dark makeup, hyperdetailed photography, soft light, ((full body)), ((3/4 view))",
refiner: true,
denoising: 0.8,
seed_number: 12345,
guidance_scale: 8,
negative_prompt: "",
num_inference_steps: 35
}
}
);
console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run alexgenovese/sdxl-custom-model using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"alexgenovese/sdxl-custom-model:a08504bd6b123bb993f648c6361041a3cc3f721a24ab6a1619b10f03dd8c0dff",
input={
"width": 1024,
"height": 1024,
"prompt": "a full body realistic photo of beautiful woman 40 y.o, walking in Madison Square Garden, smile, blue eyes, short hair, dark makeup, hyperdetailed photography, soft light, ((full body)), ((3/4 view))",
"refiner": True,
"denoising": 0.8,
"seed_number": 12345,
"guidance_scale": 8,
"negative_prompt": "",
"num_inference_steps": 35
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run alexgenovese/sdxl-custom-model 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": "a08504bd6b123bb993f648c6361041a3cc3f721a24ab6a1619b10f03dd8c0dff",
"input": {
"width": 1024,
"height": 1024,
"prompt": "a full body realistic photo of beautiful woman 40 y.o, walking in Madison Square Garden, smile, blue eyes, short hair, dark makeup, hyperdetailed photography, soft light, ((full body)), ((3/4 view))",
"refiner": true,
"denoising": 0.8,
"seed_number": 12345,
"guidance_scale": 8,
"negative_prompt": "",
"num_inference_steps": 35
}
}' \
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.
Pull and run alexgenovese/sdxl-custom-model using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/alexgenovese/sdxl-custom-model@sha256:a08504bd6b123bb993f648c6361041a3cc3f721a24ab6a1619b10f03dd8c0dff \
-i 'width=1024' \
-i 'height=1024' \
-i 'prompt="a full body realistic photo of beautiful woman 40 y.o, walking in Madison Square Garden, smile, blue eyes, short hair, dark makeup, hyperdetailed photography, soft light, ((full body)), ((3/4 view))"' \
-i 'refiner=true' \
-i 'denoising=0.8' \
-i 'seed_number=12345' \
-i 'guidance_scale=8' \
-i 'negative_prompt=""' \
-i 'num_inference_steps=35'
To learn more, take a look at the Cog documentation.
Pull and run alexgenovese/sdxl-custom-model using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/alexgenovese/sdxl-custom-model@sha256:a08504bd6b123bb993f648c6361041a3cc3f721a24ab6a1619b10f03dd8c0dff
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "a full body realistic photo of beautiful woman 40 y.o, walking in Madison Square Garden, smile, blue eyes, short hair, dark makeup, hyperdetailed photography, soft light, ((full body)), ((3/4 view))", "refiner": true, "denoising": 0.8, "seed_number": 12345, "guidance_scale": 8, "negative_prompt": "", "num_inference_steps": 35 } }' \ http://localhost:5000/predictions
Add a payment method to run this model.
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Output
{
"completed_at": "2023-11-19T12:17:51.933333Z",
"created_at": "2023-11-19T12:15:56.219475Z",
"data_removed": false,
"error": null,
"id": "b3pb7ndbun72kbscco2va666ua",
"input": {
"width": 1024,
"height": 1024,
"prompt": "a full body realistic photo of beautiful woman 40 y.o, walking in Madison Square Garden, smile, blue eyes, short hair, dark makeup, hyperdetailed photography, soft light, ((full body)), ((3/4 view))",
"refiner": true,
"denoising": 0.8,
"seed_number": 12345,
"guidance_scale": 8,
"num_inference_steps": 35
},
"logs": "Starting fp16 torch.float32 cuda\nFused all loras in UNet\nApplied correction to prompts positive a full body realistic photo of beautiful woman 40 y.o, walking in Madison Square Garden, smile, blue eyes, short hair, dark makeup, hyperdetailed photography, soft light, (full body)1.21, (3/4 view)1.21, detailed eyes, (masterpiece,best quality,ultra_detailed,highres,absurdres)1.20, 4k, professional, intricate details even to the smallest particle, extreme detail of the environment, sharp portrait, well lit, (ultra realistic, realistic)1.90, beautiful shadows, bright, photo quality, masterpiece, 8k, ultra-detailed, highly detailed, sharp focus, award winning, octane render unreal engine, volumetrics dtx, high definition, bokeh, (fashion model)1.50, (realistic, photorealistic)2.00, (fashion-forward)1.30\nApplied correction to negative prompts ,(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art)1.40, (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name)1.20, (blur, blurry, grainy)1.10, morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur)1.30, (3D ,3D Game, 3D Game Scene, 3D Character)1.10, (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities)1.30, peopleneg, unaestheticXL_Jug6\nApplied optimization\nCreated compel for prompts\nStarting inference...\ntimestep: 946 max: 3.99 min: -4.34 mean: -0.01\n 0%| | 0/28 [00:00<?, ?it/s]\ntimestep: 919 max: 4.03 min: -4.43 mean: 0.0\n 4%|▎ | 1/28 [00:01<00:35, 1.30s/it]\ntimestep: 892 max: 4.04 min: -4.39 mean: -0.01\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\ntimestep: 865 max: 4.05 min: -4.46 mean: -0.01\n 11%|█ | 3/28 [00:02<00:23, 1.06it/s]\ntimestep: 838 max: 4.04 min: -4.48 mean: -0.02\n 14%|█▍ | 4/28 [00:03<00:20, 1.15it/s]\ntimestep: 811 max: 4.04 min: -4.51 mean: -0.02\n 18%|█▊ | 5/28 [00:04<00:19, 1.20it/s]\ntimestep: 784 max: 4.04 min: -4.53 mean: -0.02\n 21%|██▏ | 6/28 [00:05<00:17, 1.24it/s]\ntimestep: 757 max: 4.03 min: -4.55mean: -0.02\n 25%|██▌ | 7/28 [00:06<00:16, 1.26it/s]\ntimestep: 730 max: 4.03 min: -4.56 mean: -0.03\n 29%|██▊ | 8/28 [00:06<00:15, 1.27it/s]\ntimestep: 703 max: 4.0 min: -4.55 mean: -0.03\n 32%|███▏ | 9/28 [00:07<00:14, 1.28it/s]\ntimestep: 676 max: 3.97 min: -4.54 mean: -0.03\n 36%|███▌ | 10/28 [00:08<00:13, 1.29it/s]\ntimestep: 649 max: 3.96 min: -4.54 mean: -0.03\n 39%|███▉ | 11/28 [00:09<00:13, 1.29it/s]\ntimestep: 622 max: 3.94 min: -4.53 mean: -0.03\n 43%|████▎ | 12/28 [00:09<00:12, 1.30it/s]\ntimestep: 595 max: 3.91 min: -4.51 mean: -0.03\n 46%|████▋ | 13/28 [00:10<00:11, 1.30it/s]\ntimestep: 568 max: 3.88 min: -4.5 mean: -0.03\n 50%|█████ | 14/28 [00:11<00:10, 1.30it/s]\ntimestep: 541 max: 3.84 min: -4.48 mean: -0.03\n 54%|█████▎ | 15/28 [00:12<00:09, 1.30it/s]\ntimestep: 514 max: 3.8 min: -4.45 mean: -0.03\n 57%|█████▋ | 16/28 [00:12<00:09, 1.30it/s]\ntimestep: 487 max: 3.75 min: -4.42 mean: -0.03\n 61%|██████ | 17/28 [00:13<00:08, 1.30it/s]\ntimestep: 460 max: 3.7 min: -4.37 mean: -0.03\n 64%|██████▍ | 18/28 [00:14<00:07, 1.31it/s]\ntimestep: 433 max: 3.64 min: -4.32 mean: -0.03\n 68%|██████▊ | 19/28 [00:15<00:06, 1.31it/s]\ntimestep: 406 max: 3.57 min: -4.27 mean: -0.03\n 71%|███████▏ | 20/28 [00:15<00:06, 1.31it/s]\ntimestep: 379 max: 3.5 min: -4.2 mean: -0.03\n 75%|███████▌ | 21/28 [00:16<00:05, 1.31it/s]\ntimestep: 352 max: 3.43 min: -4.13 mean: -0.03\n 79%|███████▊ | 22/28 [00:17<00:04, 1.31it/s]\ntimestep: 325 max: 3.36 min: -4.05 mean: -0.03\n 82%|████████▏ | 23/28 [00:18<00:03, 1.31it/s]\ntimestep: 298 max: 3.3 min: -3.96 mean: -0.03\n 86%|████████▌ | 24/28 [00:19<00:03, 1.31it/s]\ntimestep: 271 max: 3.29 min: -3.87 mean: -0.03\n 89%|████████▉ | 25/28 [00:19<00:02, 1.31it/s]\ntimestep: 244 max: 3.27 min: -3.8mean: -0.02\n 93%|█████████▎| 26/28 [00:20<00:01, 1.31it/s]\ntimestep: 217 max: 3.26 min: -3.74 mean: -0.02\n 96%|█████████▋| 27/28 [00:21<00:00, 1.31it/s]\n100%|██████████| 28/28 [00:22<00:00, 1.31it/s]\n100%|██████████| 28/28 [00:22<00:00, 1.27it/s]\ntimestep: 197 max: 3.13 min: -3.54 mean: -0.02\n 0%| | 0/8 [00:00<?, ?it/s]\ntimestep: 169 max: 3.01 min: -3.35 mean: -0.02\n 12%|█▎ | 1/8 [00:00<00:04, 1.58it/s]\ntimestep: 141 max: 2.9 min: -3.17 mean: -0.02\n 25%|██▌ | 2/8 [00:01<00:03, 1.59it/s]\ntimestep: 113 max: 2.8 min: -2.98 mean: -0.02\n 38%|███▊ | 3/8 [00:01<00:03, 1.59it/s]\ntimestep: 85 max: 2.7 min: -2.79 mean: -0.03\n 50%|█████ | 4/8 [00:02<00:02, 1.59it/s]\ntimestep: 57 max: 2.58 min: -2.58 mean: -0.03\n 62%|██████▎ | 5/8 [00:03<00:01, 1.59it/s]\ntimestep: 29 max: 2.4 min: -2.42 mean: -0.03\n 75%|███████▌ | 6/8 [00:03<00:01, 1.59it/s]\ntimestep: 1 max: 2.45 min: -2.42 mean: -0.03\n 88%|████████▊ | 7/8 [00:04<00:00, 1.59it/s]\n100%|██████████| 8/8 [00:05<00:00, 1.59it/s]\n100%|██████████| 8/8 [00:05<00:00, 1.59it/s]\nInference took: 31.832138061523438 34902",
"metrics": {
"predict_time": 32.340615,
"total_time": 115.713858
},
"output": "https://replicate.delivery/pbxt/QYKKQEkUZJLZCZ449kcbFJ3PWD56q4ht5zZJbqcHEfi3d98IA/image-34902-31.21769404411316.png",
"started_at": "2023-11-19T12:17:19.592718Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/b3pb7ndbun72kbscco2va666ua",
"cancel": "https://api.replicate.com/v1/predictions/b3pb7ndbun72kbscco2va666ua/cancel"
},
"version": "a08504bd6b123bb993f648c6361041a3cc3f721a24ab6a1619b10f03dd8c0dff"
}
Starting fp16 torch.float32 cuda
Fused all loras in UNet
Applied correction to prompts positive a full body realistic photo of beautiful woman 40 y.o, walking in Madison Square Garden, smile, blue eyes, short hair, dark makeup, hyperdetailed photography, soft light, (full body)1.21, (3/4 view)1.21, detailed eyes, (masterpiece,best quality,ultra_detailed,highres,absurdres)1.20, 4k, professional, intricate details even to the smallest particle, extreme detail of the environment, sharp portrait, well lit, (ultra realistic, realistic)1.90, beautiful shadows, bright, photo quality, masterpiece, 8k, ultra-detailed, highly detailed, sharp focus, award winning, octane render unreal engine, volumetrics dtx, high definition, bokeh, (fashion model)1.50, (realistic, photorealistic)2.00, (fashion-forward)1.30
Applied correction to negative prompts ,(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art)1.40, (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name)1.20, (blur, blurry, grainy)1.10, morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur)1.30, (3D ,3D Game, 3D Game Scene, 3D Character)1.10, (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities)1.30, peopleneg, unaestheticXL_Jug6
Applied optimization
Created compel for prompts
Starting inference...
timestep: 946 max: 3.99 min: -4.34 mean: -0.01
0%| | 0/28 [00:00<?, ?it/s]
timestep: 919 max: 4.03 min: -4.43 mean: 0.0
4%|▎ | 1/28 [00:01<00:35, 1.30s/it]
timestep: 892 max: 4.04 min: -4.39 mean: -0.01
7%|▋ | 2/28 [00:02<00:25, 1.01it/s]
timestep: 865 max: 4.05 min: -4.46 mean: -0.01
11%|█ | 3/28 [00:02<00:23, 1.06it/s]
timestep: 838 max: 4.04 min: -4.48 mean: -0.02
14%|█▍ | 4/28 [00:03<00:20, 1.15it/s]
timestep: 811 max: 4.04 min: -4.51 mean: -0.02
18%|█▊ | 5/28 [00:04<00:19, 1.20it/s]
timestep: 784 max: 4.04 min: -4.53 mean: -0.02
21%|██▏ | 6/28 [00:05<00:17, 1.24it/s]
timestep: 757 max: 4.03 min: -4.55mean: -0.02
25%|██▌ | 7/28 [00:06<00:16, 1.26it/s]
timestep: 730 max: 4.03 min: -4.56 mean: -0.03
29%|██▊ | 8/28 [00:06<00:15, 1.27it/s]
timestep: 703 max: 4.0 min: -4.55 mean: -0.03
32%|███▏ | 9/28 [00:07<00:14, 1.28it/s]
timestep: 676 max: 3.97 min: -4.54 mean: -0.03
36%|███▌ | 10/28 [00:08<00:13, 1.29it/s]
timestep: 649 max: 3.96 min: -4.54 mean: -0.03
39%|███▉ | 11/28 [00:09<00:13, 1.29it/s]
timestep: 622 max: 3.94 min: -4.53 mean: -0.03
43%|████▎ | 12/28 [00:09<00:12, 1.30it/s]
timestep: 595 max: 3.91 min: -4.51 mean: -0.03
46%|████▋ | 13/28 [00:10<00:11, 1.30it/s]
timestep: 568 max: 3.88 min: -4.5 mean: -0.03
50%|█████ | 14/28 [00:11<00:10, 1.30it/s]
timestep: 541 max: 3.84 min: -4.48 mean: -0.03
54%|█████▎ | 15/28 [00:12<00:09, 1.30it/s]
timestep: 514 max: 3.8 min: -4.45 mean: -0.03
57%|█████▋ | 16/28 [00:12<00:09, 1.30it/s]
timestep: 487 max: 3.75 min: -4.42 mean: -0.03
61%|██████ | 17/28 [00:13<00:08, 1.30it/s]
timestep: 460 max: 3.7 min: -4.37 mean: -0.03
64%|██████▍ | 18/28 [00:14<00:07, 1.31it/s]
timestep: 433 max: 3.64 min: -4.32 mean: -0.03
68%|██████▊ | 19/28 [00:15<00:06, 1.31it/s]
timestep: 406 max: 3.57 min: -4.27 mean: -0.03
71%|███████▏ | 20/28 [00:15<00:06, 1.31it/s]
timestep: 379 max: 3.5 min: -4.2 mean: -0.03
75%|███████▌ | 21/28 [00:16<00:05, 1.31it/s]
timestep: 352 max: 3.43 min: -4.13 mean: -0.03
79%|███████▊ | 22/28 [00:17<00:04, 1.31it/s]
timestep: 325 max: 3.36 min: -4.05 mean: -0.03
82%|████████▏ | 23/28 [00:18<00:03, 1.31it/s]
timestep: 298 max: 3.3 min: -3.96 mean: -0.03
86%|████████▌ | 24/28 [00:19<00:03, 1.31it/s]
timestep: 271 max: 3.29 min: -3.87 mean: -0.03
89%|████████▉ | 25/28 [00:19<00:02, 1.31it/s]
timestep: 244 max: 3.27 min: -3.8mean: -0.02
93%|█████████▎| 26/28 [00:20<00:01, 1.31it/s]
timestep: 217 max: 3.26 min: -3.74 mean: -0.02
96%|█████████▋| 27/28 [00:21<00:00, 1.31it/s]
100%|██████████| 28/28 [00:22<00:00, 1.31it/s]
100%|██████████| 28/28 [00:22<00:00, 1.27it/s]
timestep: 197 max: 3.13 min: -3.54 mean: -0.02
0%| | 0/8 [00:00<?, ?it/s]
timestep: 169 max: 3.01 min: -3.35 mean: -0.02
12%|█▎ | 1/8 [00:00<00:04, 1.58it/s]
timestep: 141 max: 2.9 min: -3.17 mean: -0.02
25%|██▌ | 2/8 [00:01<00:03, 1.59it/s]
timestep: 113 max: 2.8 min: -2.98 mean: -0.02
38%|███▊ | 3/8 [00:01<00:03, 1.59it/s]
timestep: 85 max: 2.7 min: -2.79 mean: -0.03
50%|█████ | 4/8 [00:02<00:02, 1.59it/s]
timestep: 57 max: 2.58 min: -2.58 mean: -0.03
62%|██████▎ | 5/8 [00:03<00:01, 1.59it/s]
timestep: 29 max: 2.4 min: -2.42 mean: -0.03
75%|███████▌ | 6/8 [00:03<00:01, 1.59it/s]
timestep: 1 max: 2.45 min: -2.42 mean: -0.03
88%|████████▊ | 7/8 [00:04<00:00, 1.59it/s]
100%|██████████| 8/8 [00:05<00:00, 1.59it/s]
100%|██████████| 8/8 [00:05<00:00, 1.59it/s]
Inference took: 31.832138061523438 34902