jyoung105 / pcm

Phased Consistency Model

Cold

Public
30 runs
L40S
GitHub
Weights
Paper
License

Run with an API

Playground API Examples README Versions

Prediction

jyoung105/pcm:ade7e3a05da3aef723543b16f3d5310dab761b55aadfc31a56c6d427ab4fa869

Model

jyoung105/pcm:ade7e3a0

6azat1t175rgp0cjthhbe46m3r

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

3m 38s

Created

6 months ago

Input

eta: 0
steps: 8
width: 1024
height: 1024
prompt: A man with hoodie on, illustration
clip_skip: 0
num_images: 1
guidance_scale: 6

{
  "eta": 0,
  "steps": 8,
  "width": 1024,
  "height": 1024,
  "prompt": "A man with hoodie on, illustration",
  "clip_skip": 0,
  "num_images": 1,
  "guidance_scale": 6
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run jyoung105/pcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jyoung105/pcm:ade7e3a05da3aef723543b16f3d5310dab761b55aadfc31a56c6d427ab4fa869",
  {
    input: {
      eta: 0,
      steps: 8,
      width: 1024,
      height: 1024,
      prompt: "A man with hoodie on, illustration",
      clip_skip: 0,
      num_images: 1,
      guidance_scale: 6
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run jyoung105/pcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jyoung105/pcm:ade7e3a05da3aef723543b16f3d5310dab761b55aadfc31a56c6d427ab4fa869",
    input={
        "eta": 0,
        "steps": 8,
        "width": 1024,
        "height": 1024,
        "prompt": "A man with hoodie on, illustration",
        "clip_skip": 0,
        "num_images": 1,
        "guidance_scale": 6
    }
)
print(output)

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

Run jyoung105/pcm 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": "jyoung105/pcm:ade7e3a05da3aef723543b16f3d5310dab761b55aadfc31a56c6d427ab4fa869",
    "input": {
      "eta": 0,
      "steps": 8,
      "width": 1024,
      "height": 1024,
      "prompt": "A man with hoodie on, illustration",
      "clip_skip": 0,
      "num_images": 1,
      "guidance_scale": 6
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

5.0 seconds

Tweak it ShareReport

Prediction

jyoung105/pcm:cbd659feb506c9182f6989e01572a04cbfc5956fab0c1374d9bb3cbc6de54838

Model

jyoung105/pcm:cbd659fe

ywr745qh2hrma0ck9xksy0pgbc

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

71.7s

Created

6 months ago

Input

eta: 0
seed: 2345
steps: 8
width: 1024
height: 1024
prompt: A man with hoodie on, illustration
clip_skip: 0
num_images: 1
guidance_scale: 6

{
  "eta": 0,
  "seed": 2345,
  "steps": 8,
  "width": 1024,
  "height": 1024,
  "prompt": "A man with hoodie on, illustration",
  "clip_skip": 0,
  "num_images": 1,
  "guidance_scale": 6
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run jyoung105/pcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jyoung105/pcm:cbd659feb506c9182f6989e01572a04cbfc5956fab0c1374d9bb3cbc6de54838",
  {
    input: {
      eta: 0,
      seed: 2345,
      steps: 8,
      width: 1024,
      height: 1024,
      prompt: "A man with hoodie on, illustration",
      clip_skip: 0,
      num_images: 1,
      guidance_scale: 6
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run jyoung105/pcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jyoung105/pcm:cbd659feb506c9182f6989e01572a04cbfc5956fab0c1374d9bb3cbc6de54838",
    input={
        "eta": 0,
        "seed": 2345,
        "steps": 8,
        "width": 1024,
        "height": 1024,
        "prompt": "A man with hoodie on, illustration",
        "clip_skip": 0,
        "num_images": 1,
        "guidance_scale": 6
    }
)
print(output)

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

Run jyoung105/pcm 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": "jyoung105/pcm:cbd659feb506c9182f6989e01572a04cbfc5956fab0c1374d9bb3cbc6de54838",
    "input": {
      "eta": 0,
      "seed": 2345,
      "steps": 8,
      "width": 1024,
      "height": 1024,
      "prompt": "A man with hoodie on, illustration",
      "clip_skip": 0,
      "num_images": 1,
      "guidance_scale": 6
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.1 seconds

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jyoung105 / pcm

Prediction

Input

Output

Prediction

Input

Output

Logs (6azat1t175rgp0cjthhbe46m3r)

Logs (ywr745qh2hrma0ck9xksy0pgbc)