aramintak / soft-ones

width: 1024
height: 1024
prompt: neon cyberpunk portrait on a beach, daiton style, super detailed, fine linework
lora_strength: 0.85
output_format: webp
output_quality: 80
negative_prompt: distorted, ugly, broken
number_of_images: 1

{
  "width": 1024,
  "height": 1024,
  "prompt": "neon cyberpunk portrait on a beach, daiton style, super detailed, fine linework",
  "lora_strength": 0.85,
  "output_format": "webp",
  "output_quality": 80,
  "negative_prompt": "distorted, ugly, broken",
  "number_of_images": 1
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run aramintak/soft-ones using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "neon cyberpunk portrait on a beach, daiton style, super detailed, fine linework",
      lora_strength: 0.85,
      output_format: "webp",
      output_quality: 80,
      negative_prompt: "distorted, ugly, broken",
      number_of_images: 1
    }
  }
);

// 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.

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run aramintak/soft-ones using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "neon cyberpunk portrait on a beach, daiton style, super detailed, fine linework",
        "lora_strength": 0.85,
        "output_format": "webp",
        "output_quality": 80,
        "negative_prompt": "distorted, ugly, broken",
        "number_of_images": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run aramintak/soft-ones 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": "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "neon cyberpunk portrait on a beach, daiton style, super detailed, fine linework",
      "lora_strength": 0.85,
      "output_format": "webp",
      "output_quality": 80,
      "negative_prompt": "distorted, ugly, broken",
      "number_of_images": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "completed_at": "2024-06-07T22:02:38.534391Z",
  "created_at": "2024-06-07T22:02:32.860000Z",
  "data_removed": false,
  "error": null,
  "id": "fg2vzhcg3hrgg0cfyjwvy7kj04",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "neon cyberpunk portrait on a beach, daiton style, super detailed, fine linework",
    "lora_strength": 0.85,
    "output_format": "webp",
    "output_quality": 80,
    "negative_prompt": "distorted, ugly, broken",
    "number_of_images": 1
  },
  "logs": "Random seed set to: 3628039157\nRunning workflow\ngot prompt\nExecuting node 3, title: KSampler, class type: KSampler\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:03,  5.26it/s]\n 10%|█         | 2/20 [00:00<00:03,  5.22it/s]\n 15%|█▌        | 3/20 [00:00<00:03,  5.21it/s]\n 20%|██        | 4/20 [00:00<00:03,  5.21it/s]\n 25%|██▌       | 5/20 [00:00<00:02,  5.22it/s]\n 30%|███       | 6/20 [00:01<00:02,  5.21it/s]\n 35%|███▌      | 7/20 [00:01<00:02,  5.21it/s]\n 40%|████      | 8/20 [00:01<00:02,  5.21it/s]\n 45%|████▌     | 9/20 [00:01<00:02,  5.20it/s]\n 50%|█████     | 10/20 [00:01<00:01,  5.20it/s]\n 55%|█████▌    | 11/20 [00:02<00:01,  5.20it/s]\n 60%|██████    | 12/20 [00:02<00:01,  5.20it/s]\n 65%|██████▌   | 13/20 [00:02<00:01,  5.21it/s]\n 70%|███████   | 14/20 [00:02<00:01,  5.21it/s]\n 75%|███████▌  | 15/20 [00:02<00:00,  5.21it/s]\n 80%|████████  | 16/20 [00:03<00:00,  5.20it/s]\n 85%|████████▌ | 17/20 [00:03<00:00,  5.20it/s]\n 90%|█████████ | 18/20 [00:03<00:00,  5.20it/s]\n 95%|█████████▌| 19/20 [00:03<00:00,  5.23it/s]\n100%|██████████| 20/20 [00:03<00:00,  5.26it/s]\n100%|██████████| 20/20 [00:03<00:00,  5.22it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 4.25 seconds\noutputs:  {'9': {'images': [{'filename': 'R8__00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8__00001_.png",
  "metrics": {
    "predict_time": 5.630865,
    "total_time": 5.674391
  },
  "output": [
    "https://replicate.delivery/pbxt/x5TsCUWYfhSFKSjTuYKJd3ToVsXGtMKf1VPto3es4Cv6rm4lA/R8__00001_.webp"
  ],
  "started_at": "2024-06-07T22:02:32.903526Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/fg2vzhcg3hrgg0cfyjwvy7kj04",
    "cancel": "https://api.replicate.com/v1/predictions/fg2vzhcg3hrgg0cfyjwvy7kj04/cancel"
  },
  "version": "840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15"
}

Generated in

5.6 seconds

Tweak it Share Report

Prediction

aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15

Model

aramintak/soft-ones:840dcde1

kwj1z0nvbsrgm0cfyjy86rvxxc

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

2m 7s

Created

about 1 year ago

Input

width: 1024
height: 1024
prompt: a lonesome witch walking slowly up a mountain with scattered wildflowers, daiton style, super detailed, fine linework
lora_strength: 0.85
output_format: webp
output_quality: 80
negative_prompt: bad image, zombie, bad eyes
number_of_images: 1

{
  "width": 1024,
  "height": 1024,
  "prompt": "a lonesome witch walking slowly up a mountain with scattered wildflowers, daiton style, super detailed, fine linework",
  "lora_strength": 0.85,
  "output_format": "webp",
  "output_quality": 80,
  "negative_prompt": "bad image, zombie, bad eyes",
  "number_of_images": 1
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run aramintak/soft-ones using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a lonesome witch walking slowly up a mountain with scattered wildflowers, daiton style, super detailed, fine linework",
      lora_strength: 0.85,
      output_format: "webp",
      output_quality: 80,
      negative_prompt: "bad image, zombie, bad eyes",
      number_of_images: 1
    }
  }
);

// 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.

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run aramintak/soft-ones using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a lonesome witch walking slowly up a mountain with scattered wildflowers, daiton style, super detailed, fine linework",
        "lora_strength": 0.85,
        "output_format": "webp",
        "output_quality": 80,
        "negative_prompt": "bad image, zombie, bad eyes",
        "number_of_images": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run aramintak/soft-ones 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": "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a lonesome witch walking slowly up a mountain with scattered wildflowers, daiton style, super detailed, fine linework",
      "lora_strength": 0.85,
      "output_format": "webp",
      "output_quality": 80,
      "negative_prompt": "bad image, zombie, bad eyes",
      "number_of_images": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "completed_at": "2024-06-07T22:08:07.272188Z",
  "created_at": "2024-06-07T22:06:00.542000Z",
  "data_removed": false,
  "error": null,
  "id": "kwj1z0nvbsrgm0cfyjy86rvxxc",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "a lonesome witch walking slowly up a mountain with scattered wildflowers, daiton style, super detailed, fine linework",
    "lora_strength": 0.85,
    "output_format": "webp",
    "output_quality": 80,
    "negative_prompt": "bad image, zombie, bad eyes",
    "number_of_images": 1
  },
  "logs": "Random seed set to: 3300504298\nRunning workflow\ngot prompt\nExecuting node 4, title: Load Checkpoint, class type: CheckpointLoaderSimple\nmodel_type EPS\nUsing pytorch attention in VAE\nUsing pytorch attention in VAE\nclip missing: ['clip_l.logit_scale', 'clip_l.transformer.text_projection.weight']\nloaded straight to GPU\nRequested to load SDXL\nLoading 1 new model\nExecuting node 10, title: Load LoRA, class type: LoraLoader\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nRequested to load SDXLClipModel\nLoading 1 new model\nExecuting node 7, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 5, title: Empty Latent Image, class type: EmptyLatentImage\nExecuting node 3, title: KSampler, class type: KSampler\nRequested to load SDXL\nLoading 1 new model\n  0%|          | 0/20 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.6/lib/python3.10/site-packages/torchsde/_brownian/brownian_interval.py:608: UserWarning: Should have tb<=t1 but got tb=14.614643096923828 and t1=14.614643.\nwarnings.warn(f\"Should have {tb_name}<=t1 but got {tb_name}={tb} and t1={self._end}.\")\n  5%|▌         | 1/20 [00:00<00:11,  1.62it/s]\n 10%|█         | 2/20 [00:00<00:06,  2.69it/s]\n 15%|█▌        | 3/20 [00:01<00:04,  3.44it/s]\n 20%|██        | 4/20 [00:01<00:04,  3.97it/s]\n 25%|██▌       | 5/20 [00:01<00:03,  4.33it/s]\n 30%|███       | 6/20 [00:01<00:03,  4.56it/s]\n 35%|███▌      | 7/20 [00:01<00:02,  4.75it/s]\n 40%|████      | 8/20 [00:01<00:02,  4.88it/s]\n 45%|████▌     | 9/20 [00:02<00:02,  4.97it/s]\n 50%|█████     | 10/20 [00:02<00:01,  5.03it/s]\n 55%|█████▌    | 11/20 [00:02<00:01,  5.09it/s]\n 60%|██████    | 12/20 [00:02<00:01,  5.13it/s]\n 65%|██████▌   | 13/20 [00:02<00:01,  5.16it/s]\n 70%|███████   | 14/20 [00:03<00:01,  5.18it/s]\n 75%|███████▌  | 15/20 [00:03<00:00,  5.15it/s]\n 80%|████████  | 16/20 [00:03<00:00,  5.16it/s]\n 85%|████████▌ | 17/20 [00:03<00:00,  5.18it/s]\n 90%|█████████ | 18/20 [00:03<00:00,  5.20it/s]\n 95%|█████████▌| 19/20 [00:04<00:00,  5.23it/s]\n100%|██████████| 20/20 [00:04<00:00,  5.27it/s]\n100%|██████████| 20/20 [00:04<00:00,  4.68it/s]\nRequested to load AutoencoderKL\nLoading 1 new model\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 15.29 seconds\noutputs:  {'9': {'images': [{'filename': 'R8__00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8__00001_.png",
  "metrics": {
    "predict_time": 17.366908,
    "total_time": 126.730188
  },
  "output": [
    "https://replicate.delivery/pbxt/X0eRh7sdTiTwQass0RqlIq2wNVSh9oMMj2AQima7NaGjtJeSA/R8__00001_.webp"
  ],
  "started_at": "2024-06-07T22:07:49.905280Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/kwj1z0nvbsrgm0cfyjy86rvxxc",
    "cancel": "https://api.replicate.com/v1/predictions/kwj1z0nvbsrgm0cfyjy86rvxxc/cancel"
  },
  "version": "840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15"
}

Generated in

17.4 seconds

Tweak it Share Report

Random seed set to: 3300504298
Running workflow
got prompt
Executing node 4, title: Load Checkpoint, class type: CheckpointLoaderSimple
model_type EPS
Using pytorch attention in VAE
Using pytorch attention in VAE
clip missing: ['clip_l.logit_scale', 'clip_l.transformer.text_projection.weight']
loaded straight to GPU
Requested to load SDXL
Loading 1 new model
Executing node 10, title: Load LoRA, class type: LoraLoader
Executing node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode
Requested to load SDXLClipModel
Loading 1 new model
Executing node 7, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode
Executing node 5, title: Empty Latent Image, class type: EmptyLatentImage
Executing node 3, title: KSampler, class type: KSampler
Requested to load SDXL
Loading 1 new model
  0%|          | 0/20 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.6/lib/python3.10/site-packages/torchsde/_brownian/brownian_interval.py:608: UserWarning: Should have tb<=t1 but got tb=14.614643096923828 and t1=14.614643.
warnings.warn(f"Should have {tb_name}<=t1 but got {tb_name}={tb} and t1={self._end}.")
  5%|▌         | 1/20 [00:00<00:11,  1.62it/s]
 10%|█         | 2/20 [00:00<00:06,  2.69it/s]
 15%|█▌        | 3/20 [00:01<00:04,  3.44it/s]
 20%|██        | 4/20 [00:01<00:04,  3.97it/s]
 25%|██▌       | 5/20 [00:01<00:03,  4.33it/s]
 30%|███       | 6/20 [00:01<00:03,  4.56it/s]
 35%|███▌      | 7/20 [00:01<00:02,  4.75it/s]
 40%|████      | 8/20 [00:01<00:02,  4.88it/s]
 45%|████▌     | 9/20 [00:02<00:02,  4.97it/s]
 50%|█████     | 10/20 [00:02<00:01,  5.03it/s]
 55%|█████▌    | 11/20 [00:02<00:01,  5.09it/s]
 60%|██████    | 12/20 [00:02<00:01,  5.13it/s]
 65%|██████▌   | 13/20 [00:02<00:01,  5.16it/s]
 70%|███████   | 14/20 [00:03<00:01,  5.18it/s]
 75%|███████▌  | 15/20 [00:03<00:00,  5.15it/s]
 80%|████████  | 16/20 [00:03<00:00,  5.16it/s]
 85%|████████▌ | 17/20 [00:03<00:00,  5.18it/s]
 90%|█████████ | 18/20 [00:03<00:00,  5.20it/s]
 95%|█████████▌| 19/20 [00:04<00:00,  5.23it/s]
100%|██████████| 20/20 [00:04<00:00,  5.27it/s]
100%|██████████| 20/20 [00:04<00:00,  4.68it/s]
Requested to load AutoencoderKL
Loading 1 new model
Executing node 8, title: VAE Decode, class type: VAEDecode
Executing node 9, title: Save Image, class type: SaveImage
Prompt executed in 15.29 seconds
outputs:  {'9': {'images': [{'filename': 'R8__00001_.png', 'subfolder': '', 'type': 'output'}]}}
====================================
R8__00001_.png

Prediction

aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15

Model

aramintak/soft-ones:840dcde1

j81t47d3mhrgg0cfyjzsaf094g

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

5.7s

Created

about 1 year ago

Input

width: 1024
height: 1024
prompt: a small pixie dancing in the moonlight, daiton style, super detailed, fine linework
lora_strength: 0.75
output_format: webp
output_quality: 80
negative_prompt: bad image, zombie, bad eyes
number_of_images: 1

{
  "width": 1024,
  "height": 1024,
  "prompt": "a small pixie dancing in the moonlight, daiton style, super detailed, fine linework",
  "lora_strength": 0.75,
  "output_format": "webp",
  "output_quality": 80,
  "negative_prompt": "bad image, zombie, bad eyes",
  "number_of_images": 1
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run aramintak/soft-ones using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a small pixie dancing in the moonlight, daiton style, super detailed, fine linework",
      lora_strength: 0.75,
      output_format: "webp",
      output_quality: 80,
      negative_prompt: "bad image, zombie, bad eyes",
      number_of_images: 1
    }
  }
);

// 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.

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run aramintak/soft-ones using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a small pixie dancing in the moonlight, daiton style, super detailed, fine linework",
        "lora_strength": 0.75,
        "output_format": "webp",
        "output_quality": 80,
        "negative_prompt": "bad image, zombie, bad eyes",
        "number_of_images": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run aramintak/soft-ones 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": "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a small pixie dancing in the moonlight, daiton style, super detailed, fine linework",
      "lora_strength": 0.75,
      "output_format": "webp",
      "output_quality": 80,
      "negative_prompt": "bad image, zombie, bad eyes",
      "number_of_images": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "completed_at": "2024-06-07T22:09:16.804962Z",
  "created_at": "2024-06-07T22:09:11.076000Z",
  "data_removed": false,
  "error": null,
  "id": "j81t47d3mhrgg0cfyjzsaf094g",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "a small pixie dancing in the moonlight, daiton style, super detailed, fine linework",
    "lora_strength": 0.75,
    "output_format": "webp",
    "output_quality": 80,
    "negative_prompt": "bad image, zombie, bad eyes",
    "number_of_images": 1
  },
  "logs": "Random seed set to: 1513206520\nRunning workflow\ngot prompt\nExecuting node 3, title: KSampler, class type: KSampler\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:03,  5.22it/s]\n 10%|█         | 2/20 [00:00<00:03,  5.21it/s]\n 15%|█▌        | 3/20 [00:00<00:03,  5.22it/s]\n 20%|██        | 4/20 [00:00<00:03,  5.20it/s]\n 25%|██▌       | 5/20 [00:00<00:02,  5.21it/s]\n 30%|███       | 6/20 [00:01<00:02,  5.20it/s]\n 35%|███▌      | 7/20 [00:01<00:02,  5.21it/s]\n 40%|████      | 8/20 [00:01<00:02,  5.21it/s]\n 45%|████▌     | 9/20 [00:01<00:02,  5.20it/s]\n 50%|█████     | 10/20 [00:01<00:01,  5.20it/s]\n 55%|█████▌    | 11/20 [00:02<00:01,  5.20it/s]\n 60%|██████    | 12/20 [00:02<00:01,  5.20it/s]\n 65%|██████▌   | 13/20 [00:02<00:01,  5.20it/s]\n 70%|███████   | 14/20 [00:02<00:01,  5.20it/s]\n 75%|███████▌  | 15/20 [00:02<00:00,  5.19it/s]\n 80%|████████  | 16/20 [00:03<00:00,  5.19it/s]\n 85%|████████▌ | 17/20 [00:03<00:00,  5.19it/s]\n 90%|█████████ | 18/20 [00:03<00:00,  5.19it/s]\n 95%|█████████▌| 19/20 [00:03<00:00,  5.22it/s]\n100%|██████████| 20/20 [00:03<00:00,  5.25it/s]\n100%|██████████| 20/20 [00:03<00:00,  5.21it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 4.23 seconds\noutputs:  {'9': {'images': [{'filename': 'R8__00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8__00001_.png",
  "metrics": {
    "predict_time": 5.677324,
    "total_time": 5.728962
  },
  "output": [
    "https://replicate.delivery/pbxt/r2mUfb20aqR9TiODFLx7WWFtPpfUwcZcIyQGEgAWEWXLcT8SA/R8__00001_.webp"
  ],
  "started_at": "2024-06-07T22:09:11.127638Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/j81t47d3mhrgg0cfyjzsaf094g",
    "cancel": "https://api.replicate.com/v1/predictions/j81t47d3mhrgg0cfyjzsaf094g/cancel"
  },
  "version": "840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15"
}

Generated in

5.7 seconds

Tweak it Share Report

Prediction

aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15

Model

aramintak/soft-ones:840dcde1

kryph7s6zxrgj0cfyk0a7wqmmm

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

5.8s

Created

about 1 year ago

Input

width: 1024
height: 1024
prompt: a woman with with flowers blooming from her face, daiton style, super detailed, fine linework
lora_strength: 0.75
output_format: webp
output_quality: 80
negative_prompt: bad image, zombie, bad eyes
number_of_images: 1

{
  "width": 1024,
  "height": 1024,
  "prompt": "a woman with with flowers blooming from her face, daiton style, super detailed, fine linework",
  "lora_strength": 0.75,
  "output_format": "webp",
  "output_quality": 80,
  "negative_prompt": "bad image, zombie, bad eyes",
  "number_of_images": 1
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run aramintak/soft-ones using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a woman with with flowers blooming from her face, daiton style, super detailed, fine linework",
      lora_strength: 0.75,
      output_format: "webp",
      output_quality: 80,
      negative_prompt: "bad image, zombie, bad eyes",
      number_of_images: 1
    }
  }
);

// 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.

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run aramintak/soft-ones using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a woman with with flowers blooming from her face, daiton style, super detailed, fine linework",
        "lora_strength": 0.75,
        "output_format": "webp",
        "output_quality": 80,
        "negative_prompt": "bad image, zombie, bad eyes",
        "number_of_images": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run aramintak/soft-ones 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": "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a woman with with flowers blooming from her face, daiton style, super detailed, fine linework",
      "lora_strength": 0.75,
      "output_format": "webp",
      "output_quality": 80,
      "negative_prompt": "bad image, zombie, bad eyes",
      "number_of_images": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "completed_at": "2024-06-07T22:09:50.545700Z",
  "created_at": "2024-06-07T22:09:44.703000Z",
  "data_removed": false,
  "error": null,
  "id": "kryph7s6zxrgj0cfyk0a7wqmmm",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "a woman with with flowers blooming from her face, daiton style, super detailed, fine linework",
    "lora_strength": 0.75,
    "output_format": "webp",
    "output_quality": 80,
    "negative_prompt": "bad image, zombie, bad eyes",
    "number_of_images": 1
  },
  "logs": "Random seed set to: 2893810977\nRunning workflow\ngot prompt\nExecuting node 3, title: KSampler, class type: KSampler\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:03,  5.22it/s]\n 10%|█         | 2/20 [00:00<00:03,  5.19it/s]\n 15%|█▌        | 3/20 [00:00<00:03,  5.18it/s]\n 20%|██        | 4/20 [00:00<00:03,  5.18it/s]\n 25%|██▌       | 5/20 [00:00<00:02,  5.18it/s]\n 30%|███       | 6/20 [00:01<00:02,  5.18it/s]\n 35%|███▌      | 7/20 [00:01<00:02,  5.18it/s]\n 40%|████      | 8/20 [00:01<00:02,  5.19it/s]\n 45%|████▌     | 9/20 [00:01<00:02,  5.18it/s]\n 50%|█████     | 10/20 [00:01<00:01,  5.17it/s]\n 55%|█████▌    | 11/20 [00:02<00:01,  5.01it/s]\n 60%|██████    | 12/20 [00:02<00:01,  5.06it/s]\n 65%|██████▌   | 13/20 [00:02<00:01,  5.09it/s]\n 70%|███████   | 14/20 [00:02<00:01,  5.11it/s]\n 75%|███████▌  | 15/20 [00:02<00:00,  5.12it/s]\n 80%|████████  | 16/20 [00:03<00:00,  5.13it/s]\n 85%|████████▌ | 17/20 [00:03<00:00,  5.14it/s]\n 90%|█████████ | 18/20 [00:03<00:00,  5.15it/s]\n 95%|█████████▌| 19/20 [00:03<00:00,  5.18it/s]\n100%|██████████| 20/20 [00:03<00:00,  5.22it/s]\n100%|██████████| 20/20 [00:03<00:00,  5.16it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 4.28 seconds\noutputs:  {'9': {'images': [{'filename': 'R8__00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8__00001_.png",
  "metrics": {
    "predict_time": 5.794066,
    "total_time": 5.8427
  },
  "output": [
    "https://replicate.delivery/pbxt/olbHqeNli9XcViNtYBaLkdvj5f2mPqwY8UuYOgN1CTmtcT8SA/R8__00001_.webp"
  ],
  "started_at": "2024-06-07T22:09:44.751634Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/kryph7s6zxrgj0cfyk0a7wqmmm",
    "cancel": "https://api.replicate.com/v1/predictions/kryph7s6zxrgj0cfyk0a7wqmmm/cancel"
  },
  "version": "840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15"
}

Generated in

5.8 seconds

Tweak it Share Report

Prediction

aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15

Model

aramintak/soft-ones:840dcde1

fg2vzhcg3hrgg0cfyjwvy7kj04

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

5.7s

Created

about 1 year ago by @fofr

Input

width: 1024
height: 1024
prompt: neon cyberpunk portrait on a beach, daiton style, super detailed, fine linework
lora_strength: 0.85
output_format: webp
output_quality: 80
negative_prompt: distorted, ugly, broken
number_of_images: 1

{
  "width": 1024,
  "height": 1024,
  "prompt": "neon cyberpunk portrait on a beach, daiton style, super detailed, fine linework",
  "lora_strength": 0.85,
  "output_format": "webp",
  "output_quality": 80,
  "negative_prompt": "distorted, ugly, broken",
  "number_of_images": 1
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run aramintak/soft-ones using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "neon cyberpunk portrait on a beach, daiton style, super detailed, fine linework",
      lora_strength: 0.85,
      output_format: "webp",
      output_quality: 80,
      negative_prompt: "distorted, ugly, broken",
      number_of_images: 1
    }
  }
);

// 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.

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run aramintak/soft-ones using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "neon cyberpunk portrait on a beach, daiton style, super detailed, fine linework",
        "lora_strength": 0.85,
        "output_format": "webp",
        "output_quality": 80,
        "negative_prompt": "distorted, ugly, broken",
        "number_of_images": 1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run aramintak/soft-ones 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": "aramintak/soft-ones:840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "neon cyberpunk portrait on a beach, daiton style, super detailed, fine linework",
      "lora_strength": 0.85,
      "output_format": "webp",
      "output_quality": 80,
      "negative_prompt": "distorted, ugly, broken",
      "number_of_images": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "completed_at": "2024-06-07T22:02:38.534391Z",
  "created_at": "2024-06-07T22:02:32.860000Z",
  "data_removed": false,
  "error": null,
  "id": "fg2vzhcg3hrgg0cfyjwvy7kj04",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "neon cyberpunk portrait on a beach, daiton style, super detailed, fine linework",
    "lora_strength": 0.85,
    "output_format": "webp",
    "output_quality": 80,
    "negative_prompt": "distorted, ugly, broken",
    "number_of_images": 1
  },
  "logs": "Random seed set to: 3628039157\nRunning workflow\ngot prompt\nExecuting node 3, title: KSampler, class type: KSampler\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:03,  5.26it/s]\n 10%|█         | 2/20 [00:00<00:03,  5.22it/s]\n 15%|█▌        | 3/20 [00:00<00:03,  5.21it/s]\n 20%|██        | 4/20 [00:00<00:03,  5.21it/s]\n 25%|██▌       | 5/20 [00:00<00:02,  5.22it/s]\n 30%|███       | 6/20 [00:01<00:02,  5.21it/s]\n 35%|███▌      | 7/20 [00:01<00:02,  5.21it/s]\n 40%|████      | 8/20 [00:01<00:02,  5.21it/s]\n 45%|████▌     | 9/20 [00:01<00:02,  5.20it/s]\n 50%|█████     | 10/20 [00:01<00:01,  5.20it/s]\n 55%|█████▌    | 11/20 [00:02<00:01,  5.20it/s]\n 60%|██████    | 12/20 [00:02<00:01,  5.20it/s]\n 65%|██████▌   | 13/20 [00:02<00:01,  5.21it/s]\n 70%|███████   | 14/20 [00:02<00:01,  5.21it/s]\n 75%|███████▌  | 15/20 [00:02<00:00,  5.21it/s]\n 80%|████████  | 16/20 [00:03<00:00,  5.20it/s]\n 85%|████████▌ | 17/20 [00:03<00:00,  5.20it/s]\n 90%|█████████ | 18/20 [00:03<00:00,  5.20it/s]\n 95%|█████████▌| 19/20 [00:03<00:00,  5.23it/s]\n100%|██████████| 20/20 [00:03<00:00,  5.26it/s]\n100%|██████████| 20/20 [00:03<00:00,  5.22it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 4.25 seconds\noutputs:  {'9': {'images': [{'filename': 'R8__00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8__00001_.png",
  "metrics": {
    "predict_time": 5.630865,
    "total_time": 5.674391
  },
  "output": [
    "https://replicate.delivery/pbxt/x5TsCUWYfhSFKSjTuYKJd3ToVsXGtMKf1VPto3es4Cv6rm4lA/R8__00001_.webp"
  ],
  "started_at": "2024-06-07T22:02:32.903526Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/fg2vzhcg3hrgg0cfyjwvy7kj04",
    "cancel": "https://api.replicate.com/v1/predictions/fg2vzhcg3hrgg0cfyjwvy7kj04/cancel"
  },
  "version": "840dcde1e729f762f473bbf7f5de6f02f8386d94fe8b64d320e659c32213ed15"
}

Generated in

5.6 seconds

Tweak it Share Report