MPE Engine v4.0 (Metadata Probability Extraction Engine)
This model is a token classification and span extraction transformer designed to parse release names from Torrents and Usenet.
It uses an Atomic Normalization Layer to compress relational metadata (like Season 1-5 Complete or S01E02-E04) into single, unbreakable tokens before passing them to a MiniLM encoder.
Architecture
- Backbone: sentence-transformers/all-MiniLM-L6-v2
- Head 1 (Binary): Is the token metadata? (BCE Loss)
- Head 2 (Category): What type of metadata? (Cross-Entropy Loss)
- Head 3 & 4 (Span): Start/End position of the Title (Cross-Entropy Loss)
Capabilities
- Extracts titles cleanly from Western, Anime, K-Drama, and Indian OTT release styles.
- Resists breaking on ambiguous titles like
1923, It, DV, From.
- Supports exhaustive ISO languages (3-letter codes like
tam, kor).
- Handles complete pack ranges, daily episodes, and multi-episode ranges.
Files Included
mpe_model.onnx: The production-ready ONNX export for <10ms CPU inference.pytorch_model.bin: The native PyTorch weights.tokenizer/: The WordPiece tokenizer vocabulary.categories.json: The hierarchical category mapping.
