---
language: en
tags:
- torrent
- usenet
- metadata-extraction
- title-extraction
- span-prediction
- onnx
license: mit
---

# 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.