How to use batches to test your prompts and generate content

Dan Cleary avatar
Written by Dan Cleary
Updated over a week ago

Batches are the easiest way to take a single prompt and run it many times.

Why would you want to do that?

Here are three common use cases:

  1. Prompt testing: Let's say you have a prompt that you use in your production application. With batches, you can run that single prompt many times, across many different scenarios using different variables. This allows you to do edge case testing for your prompts

  2. Faster content generation: Suppose you have a prompt that turns an article into a LinkedIn post. With batches you can easily generate 10 different LinkedIn posts about 10 different articles. All you need to do is wrap the article content in a variable, and edit the variable for each individual output.

  3. Generate data for fine tuning: This one is a little more complicated, but it's my favorite. Let's say you have a prompt that uses Few Shot learning to turn plain text into Midjourney prompts. It could look something like this.



You will help me create a training dataset for generating text to image prompts for MidJourney;

User_Input: "midjourney prompt for a Buddhist mandala with mushroom elements"

Response: "Buddhist mandala in the style of a mushroom spore print. Rich colors, deeply symbolic, arresting beauty, the key to the future of life on Earth. Highly intricate and very detailed 12K, in the style of Katsuhiro Otomo after they have rested --ar 12:16 —test"

User_Input: "midjourney prompt for a steampunk castle interior"

Response: "A blueprint of steampunk style Disney Castle, overview, building design, trending on, High-quality specular reflection, Chandeliers illuminate the floor, Copper edge, in the middle of the image, Brass pipeline, Black metal foil, Art style refer to Game Machinarium. concept design, Refer to SHAPESHIFTER CONCEPTS of artstation, cinematic, 8k, high detailed, post-processing --ar 9:5 --no dof"

User_Input: "midjourney prompt for a futuristic sound wave interface with neon colors"

Response: "Sound wave interface, psychedelic, dusty, sunset, Krakatoa smoke, detailed, realistic, vibrant, octane --ar 16:9"

User_Input: {{User_Input}}



You could then run this prompt 50 times, with different values for the {{User_Input}} to quickly create you dataset for fine tuning.

You'd have 50 high quality pairs, just like that

Here's a quick video demo of batches:

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