Official Hugging Face documentation on prompt weighting techniques in the Diffusers library, covering Compel syntax, numerical weights, blend operations, and conjunction prompts for advanced control over generation.
Hugging Face Diffusers Prompt Weighting:
1. **Compel Syntax**: Use the Compel library for precise prompt weighting
2. **Numerical Weights**: ("keyword")1.5 for emphasis in Compel
3. **Blend Operations**: Combine multiple prompts with weighted blending
4. **Conjunction Prompts**: Generate images that satisfy multiple conditions simultaneously
5. **Per-Token Control**: Weight individual tokens differently within a prompt
6. **Pipeline Integration**: Works with StableDiffusionPipeline and StableDiffusionXLPipeline
```python
from compel import Compel
compel = Compel(tokenizer=pipe.tokenizer, text_encoder=pipe.text_encoder)
prompt_embeds = compel("a cat++ playing with a ball--")
```Install the Compel library and use it with Hugging Face Diffusers pipelines for precise per-token weight control in your Python code.
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Technical deep-dive into prompt engineering covering token limits, attention mechanisms, prompt weighting with parentheses and numerical values, embedding manipulation, and A/B testing different prompt structures with reproducible experiments.
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Exhaustive guide to negative prompts covering common negative terms, negative embeddings (EasyNegative, bad_prompt), weighting strategies, model-specific negative prompts, and common mistakes like over-weighting.
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