Prediction

Model

fofr/image-prompts:ba4130c1

6uf6bm72wfcl3nrnyqbeojzb5i

Status

Succeeded

Source

Web

Hardware

–

Total duration

1.8s

Created

over 2 years ago by fofr

Webhook

–

Input

prompt: Image: a gaugin painting
max_length: 100
temperature: 1
top_p: 1
repetition_penalty: 1.5

{
  "max_length": 100,
  "prompt": "Image: a gaugin painting",
  "repetition_penalty": 1.5,
  "temperature": 1,
  "top_p": 1
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_HyX**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";

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

Run fofr/image-prompts using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/image-prompts:ba4130c13f3f1cd9771bc671bb13eab6ad5d839b2e55723b40742c03ef7f99ff",
  {
    input: {
      max_length: 100,
      prompt: "Image: a gaugin painting",
      repetition_penalty: 1.5,
      temperature: 1,
      top_p: 1
    }
  }
);

console.log(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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_HyX**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run fofr/image-prompts using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/image-prompts:ba4130c13f3f1cd9771bc671bb13eab6ad5d839b2e55723b40742c03ef7f99ff",
    input={
        "max_length": 100,
        "prompt": "Image: a gaugin painting",
        "repetition_penalty": 1.5,
        "temperature": 1,
        "top_p": 1
    }
)

# The fofr/image-prompts model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/fofr/image-prompts/api#output-schema
    print(item, end="")

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=r8_HyX**********************************

This is your API token. Keep it to yourself.

Run fofr/image-prompts 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": "fofr/image-prompts:ba4130c13f3f1cd9771bc671bb13eab6ad5d839b2e55723b40742c03ef7f99ff",
    "input": {
      "max_length": 100,
      "prompt": "Image: a gaugin painting",
      "repetition_penalty": 1.5,
      "temperature": 1,
      "top_p": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Prompt: a gaugin painting, water, the garden at sunset, fenegrean, daffodils, and an island with palm trees, 1950 --ar 3:2

Generated in

1.7 second

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