Reference
Tips and Tricks
Helpful strategies for using StreamDiffusion
Tips and Tricks
Efficient Use of CLIP Text Input
Efficient Use of CLIP Text Input
Be careful not to use too many words. CLIP (Contrastive Language-Image Pre-training) which maps text to latent space - will cut off your prompt after a certain number of characters. Focus on using important nouns and adjectives, and avoid wasting characters on lengthy sentence structure as you might with newer models like Flux, which handle more context. Keep it direct and to the point.
Balancing Prompts
Balancing Prompts
Be mindful of how each step balances the image input against the text prompt (a basic but important guideline). Experiment with strategies that emphasize prompt adherence in the early steps and become more abstract in later ones—or reverse the approach depending on your goal.
Cross-Machine Seed Consistency Considerations
Cross-Machine Seed Consistency Considerations
You can’t rely on seeds producing the same results across different machines, so avoid “locking in” a single look. Instead, ensure your prompt works well across a wide range of seeds.
Managing Texture in Image Inputs
Managing Texture in Image Inputs
Pay attention to the texture of your image input. Adding a small amount of noise can encourage the model to generate richer detail, but too much noise may result in a muddy or unclear output, so use it carefully.