Prompt Chain

Compare Text-to-Image Models

Prompt workflow for comparing text-to-image generation models using the ModelsLab API, enabling side-by-side evaluation of image outputs.

Works with modelslab

54
Spark score
out of 100
Updated 2 days ago
Version code-scan-action-0.1

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Why it matters

Evaluate and compare the performance of various text-to-image generation models. This asset helps users select the best model for their specific image generation needs by providing a structured comparison.

Outcomes

What it gets done

01

Generate images using different text-to-image models.

02

Classify and compare the quality of generated images.

03

Integrate with the ModelsLab API for model access.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/pfoo-provider-modelslab | bash

Capabilities

What this chain does

Generate images

Creates images from text prompts or templates.

Classify

Labels or categorizes text, files, or data points.

Overview

Provider Modelslab

What it does

This prompt chain orchestrates comparative testing of text-to-image generation models via the ModelsLab API. It structures a workflow that sends identical prompts to multiple models and collects their outputs, enabling direct side-by-side evaluation of different image generation engines.

How it connects

Use this when you need to benchmark text-to-image models before committing to one for production, or when evaluating which ModelsLab-supported model best matches your quality, style, or performance requirements. Ideal for teams selecting image generation capabilities for applications or content pipelines.

Source README

provider-modelslab (ModelsLab Image Generation)

Compare text-to-image generation models using the ModelsLab API.

Setup

  1. Get an API key from ModelsLab
  2. Set the environment variable:
    export MODELSLAB_API_KEY=your_api_key_here
    

Usage

npx promptfoo@latest init --example provider-modelslab
npx promptfoo@latest eval
npx promptfoo@latest view

Discussion

Questions & comments · 0

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