Prediction

ID

evtnvzdbwkbpivznf2tcy5m4ke

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

17.6s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 8.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles, deformed, mutated text, watermark
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 8.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles,  \ndeformed, mutated text, watermark",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 8.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles,  \ndeformed, mutated text, watermark",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 8.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles,  \ndeformed, mutated text, watermark",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 8.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles,  \\ndeformed, mutated text, watermark",
      "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.

Output

Generated in

15.9 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

txei5ktbn32ovyvctqv7dniqom

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

16.7s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features
refine: expert_ensemble_refiner
scheduler: KarrasDPM
lora_scale: 0.7
num_outputs: 1
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.95
negative_prompt
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
  "refine": "expert_ensemble_refiner",
  "scheduler": "KarrasDPM",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.95,
  "negative_prompt": "",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      refine: "expert_ensemble_refiner",
      scheduler: "KarrasDPM",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.95,
      negative_prompt: "",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
        "refine": "expert_ensemble_refiner",
        "scheduler": "KarrasDPM",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.95,
        "negative_prompt": "",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      "refine": "expert_ensemble_refiner",
      "scheduler": "KarrasDPM",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.95,
      "negative_prompt": "",
      "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.

Output

Generated in

14.1 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

gfbux3tbyt5zy473dwi5woosye

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

23.2s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features
refine: no_refiner
scheduler: HeunDiscrete
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.35
negative_prompt
prompt_strength: 0.8
num_inference_steps: 40

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
  "refine": "no_refiner",
  "scheduler": "HeunDiscrete",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.35,
  "negative_prompt": "",
  "prompt_strength": 0.8,
  "num_inference_steps": 40
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      refine: "no_refiner",
      scheduler: "HeunDiscrete",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.35,
      negative_prompt: "",
      prompt_strength: 0.8,
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
        "refine": "no_refiner",
        "scheduler": "HeunDiscrete",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.35,
        "negative_prompt": "",
        "prompt_strength": 0.8,
        "num_inference_steps": 40
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      "refine": "no_refiner",
      "scheduler": "HeunDiscrete",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.35,
      "negative_prompt": "",
      "prompt_strength": 0.8,
      "num_inference_steps": 40
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

22.9 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

2d6xhxlb4k7tbwnsxn7bihddsa

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

30.0s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features
refine: no_refiner
scheduler: HeunDiscrete
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.35
negative_prompt
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
  "refine": "no_refiner",
  "scheduler": "HeunDiscrete",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.35,
  "negative_prompt": "",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      refine: "no_refiner",
      scheduler: "HeunDiscrete",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.35,
      negative_prompt: "",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
        "refine": "no_refiner",
        "scheduler": "HeunDiscrete",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.35,
        "negative_prompt": "",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      "refine": "no_refiner",
      "scheduler": "HeunDiscrete",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.35,
      "negative_prompt": "",
      "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.

Output

Generated in

28.3 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

uv4frgdb27zzzay4mbvzgk3xcy

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

23.1s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features
refine: expert_ensemble_refiner
scheduler: HeunDiscrete
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.9
negative_prompt
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
  "refine": "expert_ensemble_refiner",
  "scheduler": "HeunDiscrete",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      refine: "expert_ensemble_refiner",
      scheduler: "HeunDiscrete",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
        "refine": "expert_ensemble_refiner",
        "scheduler": "HeunDiscrete",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      "refine": "expert_ensemble_refiner",
      "scheduler": "HeunDiscrete",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "",
      "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.

Output

Generated in

21.9 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

axyhcvdb32s44ehafqrigcaqzm

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

15.1s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.9
negative_prompt
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "",
      "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.

Output

Generated in

14.9 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

u3vwqflbi3ibcbsqdtv2xd2vrm

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

15.3s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.9
negative_prompt
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "",
      "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.

Output

Generated in

15.1 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

m2wmhitbynj2x7myj3adeuoyfu

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

16.4s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      "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.

Output

Generated in

15.7 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

5tka7jdbcspzz6ogaaqtkhriji

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

10.8s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch
prompt_strength: 0.8
num_inference_steps: 30

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
  "prompt_strength": 0.8,
  "num_inference_steps": 30
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      prompt_strength: 0.8,
      num_inference_steps: 30
    }
  }
);

// 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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
        "prompt_strength": 0.8,
        "num_inference_steps": 30
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

9.4 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

g3weeqdbj7owzfkgrcmn5dwdsi

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

18.5s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch
prompt_strength: 0.8
num_inference_steps: 60

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
  "prompt_strength": 0.8,
  "num_inference_steps": 60
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      prompt_strength: 0.8,
      num_inference_steps: 60
    }
  }
);

// 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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
        "prompt_strength": 0.8,
        "num_inference_steps": 60
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      "prompt_strength": 0.8,
      "num_inference_steps": 60
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

17.7 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

vrutojtbmwhb3md6xpopj2dn4a

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

21.9s

Created

over 1 year ago by @genkernel

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch
prompt_strength: 0.8
num_inference_steps: 70

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
  "prompt_strength": 0.8,
  "num_inference_steps": 70
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      prompt_strength: 0.8,
      num_inference_steps: 70
    }
  }
);

// 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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
        "prompt_strength": 0.8,
        "num_inference_steps": 70
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, a futuristic visage with cybernetic enhancements seamlessly integrated into human features",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      "prompt_strength": 0.8,
      "num_inference_steps": 70
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

20.4 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

gmwl3qtb753ezes5i5uzaadmem

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

16.8s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      "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.

Output

Generated in

15.4 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

c43nm33b4duvb7rytwphx4szku

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

24.3s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch
prompt_strength: 0.8
num_inference_steps: 80

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
  "prompt_strength": 0.8,
  "num_inference_steps": 80
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      prompt_strength: 0.8,
      num_inference_steps: 80
    }
  }
);

// 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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
        "prompt_strength": 0.8,
        "num_inference_steps": 80
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      "prompt_strength": 0.8,
      "num_inference_steps": 80
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

23.1 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

ig6f3e3bngs3gvj5kxt7lgupsq

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

16.2s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 8.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 8.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 8.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 8.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 8.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      "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.

Output

Generated in

15.0 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

ya7rrolbcaxf6vhrgb6swojgte

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

17.4s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.8
num_outputs: 1
refine_steps: null
guidance_scale: 8.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.8,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 8.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.8,
      num_outputs: 1,
      guidance_scale: 8.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.8,
        "num_outputs": 1,
        "guidance_scale": 8.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.8,
      "num_outputs": 1,
      "guidance_scale": 8.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      "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.

Output

Generated in

16.0 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

m4yqjetbv7rxumchkglnegcwzm

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

15.4s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.6
num_outputs: 1
refine_steps: null
guidance_scale: 8.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.6,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 8.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.6,
      num_outputs: 1,
      guidance_scale: 8.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.6,
        "num_outputs": 1,
        "guidance_scale": 8.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.6,
      "num_outputs": 1,
      "guidance_scale": 8.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      "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.

Output

Generated in

15.1 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

d6ccpglbn2ca7a67ijvyoiv374

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

17.0s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 8.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 8.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 8.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 8.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, wearing stylish classic suit, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 8.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      "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.

Output

Generated in

15.2 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

bvhyvvlbfqmfmkcuybh6gs2zfq

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

16.8s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 8.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 8.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 8.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 8.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 8.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      "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.

Output

Generated in

15.1 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

akkinrlbackd3twfovoofrnwv4

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

15.7s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 8.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 8.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 8.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 8.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 8.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch",
      "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.

Output

Generated in

15.1 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

j66gielb76kspech5zaxzcyhka

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

17.2s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.7
num_outputs: 1
refine_steps: null
guidance_scale: 8.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles, deformed, mutated text, watermark
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.7,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 8.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles,  \ndeformed, mutated text, watermark",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.7,
      num_outputs: 1,
      guidance_scale: 8.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles,  \ndeformed, mutated text, watermark",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.7,
        "num_outputs": 1,
        "guidance_scale": 8.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles,  \ndeformed, mutated text, watermark",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK, dressed in a halloween costume, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.7,
      "num_outputs": 1,
      "guidance_scale": 8.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles,  \\ndeformed, mutated text, watermark",
      "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.

Output

Generated in

15.8 seconds

genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e

Prediction

Model

ID

5d3okudbswu62w42mvqnvp72mi

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

16.1s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: full body, a photo of TOK, bald, dressed as a jedi from star wars, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination
refine: no_refiner
scheduler: K_EULER_ANCESTRAL
lora_scale: 0.8
num_outputs: 1
refine_steps: null
guidance_scale: 8.5
apply_watermark
high_noise_frac: 0.9
negative_prompt: worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles, deformed, mutated text, watermark
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "full body, a photo of TOK, bald, dressed as a jedi from star wars, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
  "refine": "no_refiner",
  "scheduler": "K_EULER_ANCESTRAL",
  "lora_scale": 0.8,
  "num_outputs": 1,
  "refine_steps": null,
  "guidance_scale": 8.5,
  "apply_watermark": false,
  "high_noise_frac": 0.9,
  "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles,  \ndeformed, mutated text, watermark",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

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 genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "full body, a photo of TOK, bald, dressed as a jedi from star wars, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      lora_scale: 0.8,
      num_outputs: 1,
      guidance_scale: 8.5,
      apply_watermark: false,
      high_noise_frac: 0.9,
      negative_prompt: "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles,  \ndeformed, mutated text, watermark",
      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

Import the client:

import replicate

Run genkernel/headshot-public using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "full body, a photo of TOK, bald, dressed as a jedi from star wars, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "lora_scale": 0.8,
        "num_outputs": 1,
        "guidance_scale": 8.5,
        "apply_watermark": False,
        "high_noise_frac": 0.9,
        "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles,  \ndeformed, mutated text, watermark",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run genkernel/headshot-public 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": "genkernel/headshot-public:f889ba013f4785999ac7c260c556e8af4591385fe6e9d269f04098b5f0e7293e",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "full body, a photo of TOK, bald, dressed as a jedi from star wars, RAW photo, subject, 8k uhd, dslr, soft lighting, high quality, clearly face, clear facial features, 35mm lens, f/1.8, natural lighting, global illumination",
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "lora_scale": 0.8,
      "num_outputs": 1,
      "guidance_scale": 8.5,
      "apply_watermark": false,
      "high_noise_frac": 0.9,
      "negative_prompt": "worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch, text, watermark, medium quality, blurry, censored, wrinkles,  \\ndeformed, mutated text, watermark",
      "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.

Output

Generated in

14.9 seconds