Deformed generations, particularly on human body parts (e.g. hands, feet), are a common issue with many models. This can be dealt with to some extent with good negative prompts. The following example is adapted from this Reddit post.
Using Stable Diffusion v1.5 and the following prompt, we generate a nice image of Brad Pitt, except for his hands of course!
Using a robust negative prompt, we can generate much more convincing hands.
Using a similar negative prompt can help with other body parts as well. Unfortunately, this technique is not consistent, so you may need to attempt multiple generations before getting a good result. In the future, this type of prompting should be unnecessary since models will improve. However, currently it is a very useful technique.
Improved models such as Protogen are often better with hands, feet, etc.
Sander Schulhoff is the Founder of Learn Prompting and an ML Researcher at the University of Maryland. He created the first open-source Prompt Engineering guide, reaching 3M+ people and teaching them to use tools like ChatGPT. Sander also led a team behind Prompt Report, the most comprehensive study of prompting ever done, co-authored with researchers from the University of Maryland, OpenAI, Microsoft, Google, Princeton, Stanford, and other leading institutions. This 76-page survey analyzed 1,500+ academic papers and covered 200+ prompting techniques.
Blake. (2022). With the right prompt, Stable Diffusion 2.0 can do hands. https://www.reddit.com/r/StableDiffusion/comments/z7salo/with_the_right_prompt_stable_diffusion_20_can_do/ ↩