Midjourney without Midjourney… @prompthero has fine-tuned Stable Diffusion so you can create images in the style of Midjourney, but with an open source model. You can run it on the web or via an API on Replicate:
PROMPT ENGINEERING
-
Training data presence affects image generation result interest
By
–
It is possible that images like this were in the training set, in which case the result is indeed less interesting. Would be good to know.
-

Astronaut Riding Horse: DALL-E’s Remarkable Pose Accuracy
By
–
What's remarkable about this image is that the astronaut is in the correct riding pose, even though DALL-E has presumably never seen "an astronaut riding a horse" as prompted.
-
AI Art Prompts Artists to Create New Distinctive Styles
By
–
Like the Impressionism movement that emerged with the popularisation of photography (increasingly used to "capture" realistic scenes), artists in the 2020s felt the need to define new styles to distinguish themselves from the art produced by #AI generators.
-
AI Generates Book Synopses: Try Our New Creative Tool
By
–
Earlier this week, the world celebrated International Book Lovers Day. So this week's preset is all about books. Enter a book name (make something up!) and our AI model will generate a synopsis. Try it out yourself in our Playground – https://t.co/30GOP00ZU1 pic.twitter.com/syk61GjCx1
— Cohere (@cohere) 11 novembre 2022Earlier this week, the world celebrated International Book Lovers Day. So this week's preset is all about books. Enter a book name (make something up!) and our AI model will generate a synopsis. Try it out yourself in our Playground – https://
hubs.li/Q01s6X8t0 -

Model Capabilities Emerge with Scale: Sentiment Classification Study
By
–
This is a wonderful study on the emergence of model capabilities with scale. It is remarkable to see sentiment classification working with 1 data point, and fascinating to see the effectiveness of chain of thought prompting growing with scale.
-
Multiple prompts and fine-tunes serve different AI purposes
By
–
Depends! We have many prompts and fine-tunes in place, each with a different purpose, some working together.
-
GPT performance varies significantly by use case
By
–
Like most things with GPT, it’s super case by case
-
Prompt Examples: Impact on Model Performance and Variation
By
–
Depends on the prompt! More examples is especially helpful when the examples relate to one another and contain explicit information to inform future generations. But too many examples can lead to decreased performance and variation in responses.
-
Writing Effective AI Prompts: Language Skills and Formatting
By
–
For example, my go-to is to provide instructions in plain English, then examples in JSON for easy parsing. I’ve seen others use English for everything. Or markdown. One thing is clear though — great language + reasoning skills are necessary to write good prompts.