Stable Diffusion 2.0 and the Importance of Negative Prompts for Good Results. Stable Diffusion 2.0 is out, and it’s a very different model from 1.4/1.5. It’s trained using a new text encoder (OpenCLIP, in place of OpenAI’s CLIP) which means a lot of the old tricks—notably using “Greg Rutkowski” to get high quality fantasy art—no longer work. What DOES work, incredibly well, is negative prompting—saying things like “cyberpunk forest by Salvador Dali” but negative on “trees, green”. Max Woolf explores negative prompting in depth in this article, including how to combine it with textual inversion.
Recent articles
- llm cmd undo last git commit - a new plugin for LLM - 26th March 2024
- Building and testing C extensions for SQLite with ChatGPT Code Interpreter - 23rd March 2024
- Claude and ChatGPT for ad-hoc sidequests - 22nd March 2024
- Weeknotes: the aftermath of NICAR - 16th March 2024
- The GPT-4 barrier has finally been broken - 8th March 2024
- Prompt injection and jailbreaking are not the same thing - 5th March 2024