goodguy1963/hidream-l1-full-img2img:d5f410b4 | Run with an API on Replicate

Version

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goodguy1963 /hidream-l1-full-img2img:d5f410b4

Playground API

Input

image

file

Input image file (required)

prompt_prefix

string

Shift + Return to add a new line

Custom prompt prefix to prepend to the Florence-2 generated caption

Default: "Photo"

seed

integer

Random seed

Default: 42

steps

integer

(minimum: 1, maximum: 100)

Number of inference steps

Default: 50

cfg

number

(minimum: 1, maximum: 20)

Guidance scale

Default: 5.54

denoise

number

(minimum: 0, maximum: 1)

Denoising strength

Default: 0.6

sampler_name

string

Sampling algorithm to use

Default: "uni_pc"

scheduler

string

Scheduler for the sampler

Default: "normal"

Run this model in Node.js with one line of code:

npx create-replicate --model=goodguy1963/hidream-l1-full-img2img

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

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 goodguy1963/hidream-l1-full-img2img using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "goodguy1963/hidream-l1-full-img2img:d5f410b46a515d1875f3e2d11e3fc660da2dd9b917cd58c00c26c7132ce410e0",
  {
    input: {
      cfg: 5.54,
      seed: 42,
      steps: 50,
      denoise: 0.6,
      scheduler: "normal",
      sampler_name: "uni_pc",
      prompt_prefix: "Photo"
    }
  }
);

// 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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run goodguy1963/hidream-l1-full-img2img using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "goodguy1963/hidream-l1-full-img2img:d5f410b46a515d1875f3e2d11e3fc660da2dd9b917cd58c00c26c7132ce410e0",
    input={
        "cfg": 5.54,
        "seed": 42,
        "steps": 50,
        "denoise": 0.6,
        "scheduler": "normal",
        "sampler_name": "uni_pc",
        "prompt_prefix": "Photo"
    }
)
print(output)

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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run goodguy1963/hidream-l1-full-img2img 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": "goodguy1963/hidream-l1-full-img2img:d5f410b46a515d1875f3e2d11e3fc660da2dd9b917cd58c00c26c7132ce410e0",
    "input": {
      "cfg": 5.54,
      "seed": 42,
      "steps": 50,
      "denoise": 0.6,
      "scheduler": "normal",
      "sampler_name": "uni_pc",
      "prompt_prefix": "Photo"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

No output yet! Press "Submit" to start a prediction.