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mpe-release-parserv2
de-slothbug/mpe-release-parserv2
mpe-release-parserv2 is a machine learning model from de-slothbug. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
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 Com…
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Updated Jul 16, 2026
Repo size
204 MB
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.onnx113 MB · 55%
At a glance
- License
- mit
- Access
- Public
- Created
- Jul 16, 2026
- Updated
- Jul 16, 2026
- SHA
- d37b38b2
Model card
From the Hugging Face model README
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.
- License
- mit
- Languages
- en
- Created
- Jul 16, 2026
- Updated
- Jul 16, 2026