Downloads · 30 days
0
wrathofgod/narrative-context-m2
narrative-context-m2 is a machine learning model from wrathofgod. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Cross-scene feature evolution Transformer for film narrative understanding. Consumes 256-d scene embeddings from wrathofgod/scene-perception-m1-unfreeze-deberta-small.
Downloads · 30 days
0
Access
Public
Updated Apr 10, 2026
Repo size
33.1 MB
Likes
0
Public
Click a slice to open those files.
.pt33.1 MB · 100%
From the Hugging Face model README
Cross-scene feature evolution Transformer for film narrative understanding.
Consumes 256-d scene embeddings from wrathofgod/scene-perception-m1-unfreeze-deberta-small.
| Component | Old M2 | New M2 |
|---|---|---|
| Feature dim | 304-d | 308-d (sin/cos position) |
| Positional encoding | window-relative only | window-relative + film-absolute MLP |
| Feature evolution | none | DeltaEncoder (GLU) as extra token |
| Sequence length | 5 | 7 ([CLS] + 5 scenes + [DELTA]) |
| Context fusion | last token only | CLS ⊕ current-scene via fusion gate |
| Transformer depth | 4L × 8H, FFN=512 | 6L × 8H, FFN=768 |
| Label smoothing | none | ε=0.1 |
5-scene causal window [t-4 … t] per film. Per-scene feature: 305-d (M1 embedding + metadata + sin/cos position). Film position (0-1 scalar) fed separately to FilmPositionEncoder.
| # | Head | Type | Output |
|---|---|---|---|
| 1 | scene_valence_continuous | regression | -1.0 to 1.0 |
| 2 | tension_level | regression | 1 to 10 |
| 3 | arousal_level | regression | 1 to 10 |
| 4 | emotional_shift_trigger | binary | True / False |
| 5 | narrative_arc_position | 5-class | Setup / Rising / Climax / Falling / Resolution |
| 6 | foreshadowing_type | 4-class | None / Foreshadow / Payoff / Echo |
| 7 | transition_type | 5-class | attacca / fade / segue / silence / cut |