prunaai / hidream-l1-full

This is an optimised version of the hidream-full model using the pruna ai optimisation toolkit!

Cold

Public
6.8K runs
A100 (80GB)

Iterate in playground

Run with an API

Playground API Examples README Versions

Prediction

prunaai/hidream-l1-full:70e52dbcff0149b38a2d1006427c5d35471e90010b1355220e40574fbef306fb

Model

prunaai/hidream-l1-full:70e52dbc

3mb3z8qqr5rj00cp3zmbansmmm

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

24.3s

Created

about 1 month ago

Input

seed: 1
prompt: a purple cheetah holding a sign that says "pip install pruna"
model_type: full
resolution: 1024 × 1024 (Square)
speed_mode: Juiced 🔥 (more speed)
output_format: webp
output_quality: 80

{
  "seed": 1,
  "prompt": "a purple cheetah holding a sign that says \"pip install pruna\"",
  "model_type": "full",
  "resolution": "1024 × 1024 (Square)",
  "speed_mode": "Juiced 🔥 (more speed)",
  "output_format": "webp",
  "output_quality": 80
}

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

const output = await replicate.run(
  "prunaai/hidream-l1-full:70e52dbcff0149b38a2d1006427c5d35471e90010b1355220e40574fbef306fb",
  {
    input: {
      seed: 1,
      prompt: "a purple cheetah holding a sign that says \"pip install pruna\"",
      model_type: "full",
      resolution: "1024 × 1024 (Square)",
      speed_mode: "Juiced 🔥 (more speed)",
      output_format: "webp",
      output_quality: 80
    }
  }
);

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

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

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

output = replicate.run(
    "prunaai/hidream-l1-full:70e52dbcff0149b38a2d1006427c5d35471e90010b1355220e40574fbef306fb",
    input={
        "seed": 1,
        "prompt": "a purple cheetah holding a sign that says \"pip install pruna\"",
        "model_type": "full",
        "resolution": "1024 × 1024 (Square)",
        "speed_mode": "Juiced 🔥 (more speed)",
        "output_format": "webp",
        "output_quality": 80
    }
)
print(output)

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

Run prunaai/hidream-l1-full 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": "prunaai/hidream-l1-full:70e52dbcff0149b38a2d1006427c5d35471e90010b1355220e40574fbef306fb",
    "input": {
      "seed": 1,
      "prompt": "a purple cheetah holding a sign that says \\"pip install pruna\\"",
      "model_type": "full",
      "resolution": "1024 × 1024 (Square)",
      "speed_mode": "Juiced 🔥 (more speed)",
      "output_format": "webp",
      "output_quality": 80
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

24.3 seconds

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