Readme
This model doesn't have a readme.
DreamBooth safetensors model use RealVisXL
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 zelenioncode/custum_model_safetonsors using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"zelenioncode/custum_model_safetonsors:eef480e5d1bbed213f523e8f49ae4a34e853361a0b177e0cffa5b081e3246429",
{
input: {
seed: 3456051406,
width: 768,
height: 1024,
prompt: "photograph of casual sophisticated ohwx woman, looking camera, classic side part, tailored black three-piece suit,skin imperfections, 8k uhd, dsir, soft lighting, high quality, film grain, Fujifilm XT3",
scheduler: "DDIM",
safetensors: "https://huggingface.co/WGlint/sfya_ReaVis_V5.1_noVAE/blob/main/sfya_rv.safetensors",
guidance_scale: 7,
number_picture: 4,
negative_prompt: "Tattoos, (deformed iris, deformed pupils, semi-realistic, gi, 3d, render, sketch, cartoon, drawing, anime), text, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, UnrealisticDream",
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 zelenioncode/custum_model_safetonsors using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"zelenioncode/custum_model_safetonsors:eef480e5d1bbed213f523e8f49ae4a34e853361a0b177e0cffa5b081e3246429",
input={
"seed": 3456051406,
"width": 768,
"height": 1024,
"prompt": "photograph of casual sophisticated ohwx woman, looking camera, classic side part, tailored black three-piece suit,skin imperfections, 8k uhd, dsir, soft lighting, high quality, film grain, Fujifilm XT3",
"scheduler": "DDIM",
"safetensors": "https://huggingface.co/WGlint/sfya_ReaVis_V5.1_noVAE/blob/main/sfya_rv.safetensors",
"guidance_scale": 7,
"number_picture": 4,
"negative_prompt": "Tattoos, (deformed iris, deformed pupils, semi-realistic, gi, 3d, render, sketch, cartoon, drawing, anime), text, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, UnrealisticDream",
"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 zelenioncode/custum_model_safetonsors 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": "zelenioncode/custum_model_safetonsors:eef480e5d1bbed213f523e8f49ae4a34e853361a0b177e0cffa5b081e3246429",
"input": {
"seed": 3456051406,
"width": 768,
"height": 1024,
"prompt": "photograph of casual sophisticated ohwx woman, looking camera, classic side part, tailored black three-piece suit,skin imperfections, 8k uhd, dsir, soft lighting, high quality, film grain, Fujifilm XT3",
"scheduler": "DDIM",
"safetensors": "https://huggingface.co/WGlint/sfya_ReaVis_V5.1_noVAE/blob/main/sfya_rv.safetensors",
"guidance_scale": 7,
"number_picture": 4,
"negative_prompt": "Tattoos, (deformed iris, deformed pupils, semi-realistic, gi, 3d, render, sketch, cartoon, drawing, anime), text, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, UnrealisticDream",
"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/zelenioncode/custum_model_safetonsors@sha256:eef480e5d1bbed213f523e8f49ae4a34e853361a0b177e0cffa5b081e3246429 \
-i 'seed=3456051406' \
-i 'width=768' \
-i 'height=1024' \
-i 'prompt="photograph of casual sophisticated ohwx woman, looking camera, classic side part, tailored black three-piece suit,skin imperfections, 8k uhd, dsir, soft lighting, high quality, film grain, Fujifilm XT3"' \
-i 'scheduler="DDIM"' \
-i 'safetensors="https://huggingface.co/WGlint/sfya_ReaVis_V5.1_noVAE/blob/main/sfya_rv.safetensors"' \
-i 'guidance_scale=7' \
-i 'number_picture=4' \
-i 'negative_prompt="Tattoos, (deformed iris, deformed pupils, semi-realistic, gi, 3d, render, sketch, cartoon, drawing, anime), text, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, UnrealisticDream"' \
-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/zelenioncode/custum_model_safetonsors@sha256:eef480e5d1bbed213f523e8f49ae4a34e853361a0b177e0cffa5b081e3246429
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "seed": 3456051406, "width": 768, "height": 1024, "prompt": "photograph of casual sophisticated ohwx woman, looking camera, classic side part, tailored black three-piece suit,skin imperfections, 8k uhd, dsir, soft lighting, high quality, film grain, Fujifilm XT3", "scheduler": "DDIM", "safetensors": "https://huggingface.co/WGlint/sfya_ReaVis_V5.1_noVAE/blob/main/sfya_rv.safetensors", "guidance_scale": 7, "number_picture": 4, "negative_prompt": "Tattoos, (deformed iris, deformed pupils, semi-realistic, gi, 3d, render, sketch, cartoon, drawing, anime), text, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, UnrealisticDream", "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 $0.088. Alternatively, try out our featured models for free.
By signing in, you agree to our
terms of service and privacy policy
{
"completed_at": "2023-12-17T19:59:21.786786Z",
"created_at": "2023-12-17T19:59:06.046473Z",
"data_removed": false,
"error": null,
"id": "5kse7pdbe7m4h4hbu4ekveqt5e",
"input": {
"seed": 3456051406,
"width": 768,
"height": 1024,
"prompt": "photograph of casual sophisticated ohwx woman, looking camera, classic side part, tailored black three-piece suit,skin imperfections, 8k uhd, dsir, soft lighting, high quality, film grain, Fujifilm XT3",
"WithRVXL": true,
"guidance_scale": 7,
"number_picture": 4,
"negative_prompt": "Tattoos, (deformed iris, deformed pupils, semi-realistic, gi, 3d, render, sketch, cartoon, drawing, anime), text, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, UnrealisticDream",
"num_inference_steps": 40
},
"logs": "0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:12, 3.17it/s]\n 5%|▌ | 2/40 [00:00<00:11, 3.27it/s]\n 8%|▊ | 3/40 [00:00<00:11, 3.30it/s]\n 10%|█ | 4/40 [00:01<00:10, 3.31it/s]\n 12%|█▎ | 5/40 [00:01<00:10, 3.32it/s]\n 15%|█▌ | 6/40 [00:01<00:10, 3.33it/s]\n 18%|█▊ | 7/40 [00:02<00:09, 3.33it/s]\n 20%|██ | 8/40 [00:02<00:09, 3.33it/s]\n 22%|██▎ | 9/40 [00:02<00:09, 3.32it/s]\n 25%|██▌ | 10/40 [00:03<00:09, 3.32it/s]\n 28%|██▊ | 11/40 [00:03<00:08, 3.32it/s]\n 30%|███ | 12/40 [00:03<00:08, 3.32it/s]\n 32%|███▎ | 13/40 [00:03<00:08, 3.32it/s]\n 35%|███▌ | 14/40 [00:04<00:07, 3.33it/s]\n 38%|███▊ | 15/40 [00:04<00:07, 3.33it/s]\n 40%|████ | 16/40 [00:04<00:07, 3.33it/s]\n 42%|████▎ | 17/40 [00:05<00:06, 3.33it/s]\n 45%|████▌ | 18/40 [00:05<00:06, 3.33it/s]\n 48%|████▊ | 19/40 [00:05<00:06, 3.32it/s]\n 50%|█████ | 20/40 [00:06<00:06, 3.32it/s]\n 52%|█████▎ | 21/40 [00:06<00:05, 3.32it/s]\n 55%|█████▌ | 22/40 [00:06<00:05, 3.32it/s]\n 57%|█████▊ | 23/40 [00:06<00:05, 3.32it/s]\n 60%|██████ | 24/40 [00:07<00:04, 3.32it/s]\n 62%|██████▎ | 25/40 [00:07<00:04, 3.32it/s]\n 65%|██████▌ | 26/40 [00:07<00:04, 3.32it/s]\n 68%|██████▊ | 27/40 [00:08<00:03, 3.32it/s]\n 70%|███████ | 28/40 [00:08<00:03, 3.32it/s]\n 72%|███████▎ | 29/40 [00:08<00:03, 3.32it/s]\n 75%|███████▌ | 30/40 [00:09<00:03, 3.32it/s]\n 78%|███████▊ | 31/40 [00:09<00:02, 3.32it/s]\n 80%|████████ | 32/40 [00:09<00:02, 3.32it/s]\n 82%|████████▎ | 33/40 [00:09<00:02, 3.32it/s]\n 85%|████████▌ | 34/40 [00:10<00:01, 3.32it/s]\n 88%|████████▊ | 35/40 [00:10<00:01, 3.32it/s]\n 90%|█████████ | 36/40 [00:10<00:01, 3.32it/s]\n 92%|█████████▎| 37/40 [00:11<00:00, 3.32it/s]\n 95%|█████████▌| 38/40 [00:11<00:00, 3.32it/s]\n 98%|█████████▊| 39/40 [00:11<00:00, 3.32it/s]\n100%|██████████| 40/40 [00:12<00:00, 3.32it/s]\n100%|██████████| 40/40 [00:12<00:00, 3.32it/s]\nStableDiffusionXLPipeline {\n\"_class_name\": \"StableDiffusionXLPipeline\",\n\"_diffusers_version\": \"0.24.0\",\n\"feature_extractor\": [\nnull,\nnull\n],\n\"force_zeros_for_empty_prompt\": true,\n\"image_encoder\": [\nnull,\nnull\n],\n\"scheduler\": [\n\"diffusers\",\n\"EulerDiscreteScheduler\"\n],\n\"text_encoder\": [\n\"transformers\",\n\"CLIPTextModel\"\n],\n\"text_encoder_2\": [\n\"transformers\",\n\"CLIPTextModelWithProjection\"\n],\n\"tokenizer\": [\n\"transformers\",\n\"CLIPTokenizer\"\n],\n\"tokenizer_2\": [\n\"transformers\",\n\"CLIPTokenizer\"\n],\n\"unet\": [\n\"diffusers\",\n\"UNet2DConditionModel\"\n],\n\"vae\": [\n\"diffusers\",\n\"AutoencoderKL\"\n]\n}",
"metrics": {
"predict_time": 15.723499,
"total_time": 15.740313
},
"output": [
"https://replicate.delivery/pbxt/vxbYdrEID9oAKBEpMtcz7EP7ECPZPHdaU6EpR7C9AcHGF0gE/output_0.png",
"https://replicate.delivery/pbxt/zttINejIQUWsUSosGtlYQ5x9DzMPaKi5o2ZAjfQJwEPZUQDSA/output_1.png",
"https://replicate.delivery/pbxt/SNfXIDcPp2y7KyiTUkx5Zf6oxTWYjIzdD2Txm5eP6sdyogGkA/output_2.png",
"https://replicate.delivery/pbxt/3qczqSwKJLZAD9Q1APpaTwJVWodS68ab5cNyNwOyhMZGF0gE/output_3.png"
],
"started_at": "2023-12-17T19:59:06.063287Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/5kse7pdbe7m4h4hbu4ekveqt5e",
"cancel": "https://api.replicate.com/v1/predictions/5kse7pdbe7m4h4hbu4ekveqt5e/cancel"
},
"version": "fbc6b8aa2b270d55b81836e4feee38c2f1051e79c6f414aa7ede98af5ef25781"
}
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StableDiffusionXLPipeline {
"_class_name": "StableDiffusionXLPipeline",
"_diffusers_version": "0.24.0",
"feature_extractor": [
null,
null
],
"force_zeros_for_empty_prompt": true,
"image_encoder": [
null,
null
],
"scheduler": [
"diffusers",
"EulerDiscreteScheduler"
],
"text_encoder": [
"transformers",
"CLIPTextModel"
],
"text_encoder_2": [
"transformers",
"CLIPTextModelWithProjection"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"tokenizer_2": [
"transformers",
"CLIPTokenizer"
],
"unet": [
"diffusers",
"UNet2DConditionModel"
],
"vae": [
"diffusers",
"AutoencoderKL"
]
}
This output was created using a different version of the model, zelenioncode/custum_model_safetonsors:fbc6b8aa.
This model costs approximately $0.088 to run on Replicate, or 11 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 91 seconds. The predict time for this model varies significantly based on the inputs.
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.
This model costs approximately $0.088 to run on Replicate, but this varies depending on your inputs. View more.
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StableDiffusionXLPipeline {
"_class_name": "StableDiffusionXLPipeline",
"_diffusers_version": "0.24.0",
"feature_extractor": [
null,
null
],
"force_zeros_for_empty_prompt": true,
"image_encoder": [
null,
null
],
"scheduler": [
"diffusers",
"EulerDiscreteScheduler"
],
"text_encoder": [
"transformers",
"CLIPTextModel"
],
"text_encoder_2": [
"transformers",
"CLIPTextModelWithProjection"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"tokenizer_2": [
"transformers",
"CLIPTokenizer"
],
"unet": [
"diffusers",
"UNet2DConditionModel"
],
"vae": [
"diffusers",
"AutoencoderKL"
]
}