Skip to content

Latest commit

 

History

History
44 lines (35 loc) · 2.52 KB

TAGS_GUIDE.md

File metadata and controls

44 lines (35 loc) · 2.52 KB

HeartMuLa - Tags Guide (Prompt Engineering)

This guide is based on the analysis of the HeartMuLa research paper (Sections 3.2 & 6.2). The model uses a natural language tokenizer (Llama 3) rather than a fixed dictionary. To achieve stable generation, select tags from the 8 primary categories used during training.

The 8 Pillars of Training

Each category has an Importance percentage representing its "Selection Probability" during training.

  • Training Frequency: Tags were "sampled" during training. Genre was included 95% of the time, while Instrument was only included 25%.
  • Model Expectations: The model expects a Genre tag to function correctly. Without it, the generation lacks a clear structural anchor.
  • Influence vs. Stability: Higher percentages equal higher stability. A 95% tag (Genre) is a "Strong Anchor," while a 10% tag (Topic) is a "Weak Hint" that may be ignored if it conflicts with stronger tags.
  • The Strategy: For maximum control, lean heavily on the top 4 categories (Genre, Timbre, Gender, Mood). Use lower-percentage tags only as "seasoning" once the main structure is set.

Official Categories

  1. GENRE (95% - MANDATORY) Examples: Pop, Rock, Electronic, Hiphop, Jazz, Classical, Techno, Trance, Ambient.
  2. TIMBRE (50% - Sound Texture) Examples: Soft, Warm, Husky, Bright, Dark, Distorted.
  3. GENDER (37% - Vocal Character) Examples: Male, Female.
  4. MOOD (32% - Emotional Vibe) Examples: Happy, Sad, Energetic, Joyful, Melancholic, Relaxing, Dark.
  5. INSTRUMENT (25% - Dominant Sounds) Examples: Piano, Synthesizer, Acoustic Guitar, Electric Guitar, Bass, Drums, Strings, Violin.
  6. SCENE (20% - Listening Context) Examples: Dance, Workout, Dating, Study, Cinematic, Party.
  7. REGION (12% - Cultural Influence) Examples: K-pop, Latin, Western.
  8. TOPIC (10% - Lyrical Theme) Examples: Love, Summer, Heartbreak.

Prompting Strategy: "Less is More"

To maintain a strong anchor and avoid "Probability Interference," avoid conflicting tags.

  • Semantic Conflict: Prompting "Rock, Jazz" splits the model's attention, often resulting in "muddy" or generic arrangements.
  • Anchor Stability: One strong anchor provides a clear map. Multiple genres create conflicting maps, causing the AI to lose focus.
  • Recommendation: Select only one tag per category. Be precise rather than broad.

Recommended Format

Use a comma-separated list.

Examples:

  • Electronic, Techno, Synthesizer, Dark, High Energy, Club
  • Pop, Piano, Female, Sad, Soft, Love, Acoustic