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bert-torrent-nsfw – AI Model by lelloman | AlphaNeural AI
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lelloman
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bert-torrent-nsfw
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onnx
text-classification
bert
torrent
nsfw-detection
en
mit
us
not-for-all-audiences
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BERT Torrent NSFW Classifier
A BERT-tiny binary classifier for detecting NSFW content in torrent names and file listings.
Model Details
Architecture:
BERT-tiny (2 layers, 128 hidden, 2 attention heads)
Task:
Binary classification (safe vs nsfw)
Input:
Torrent name + top 3 filenames by size
Output:
Logits for [safe, nsfw]
Format:
ONNX (embedded weights)
Size:
~17MB
Usage
This model is designed to be used with
mimmo
, a Rust-based torrent content classifier.
bash
1
# With mimmo CLI
2
mimmo --detect-nsfw
"Torrent.Name.Here"
Training
Trained on a dataset of ~10k torrent names labeled as safe/nsfw using:
BERT-tiny base model
Binary cross-entropy loss
AdamW optimizer
Performance
The model is used as a fallback after keyword and pattern matching stages:
Keywords
- HashSet lookup for explicit terms (confidence: 0.95)
Patterns
- Regex for JAV codes, studio patterns (confidence: 0.90)
ML (this model)
- For ambiguous cases
Limitations
Trained primarily on English torrent names
May not catch all NSFW content, especially with obfuscated names
Should be used in combination with keyword/pattern stages for best results
License
MIT
