Simple Narrative Edge Segmenter — a ModernBERT-based scene/chapter boundary detector
Project description
SNES — Simple Narrative Edge Segmenter
ModernBERT-based scene/chapter boundary detector for narrative text.
SNES predicts paragraph-level transitions (edges) in long-form documents using an encoder with 8k token context.
Install
pip install -e .
Requires Python 3.10+ and the dependencies listed in pyproject.toml.
Quick Start
Train:
snes-train --train_file data/train.jsonl --val_file data/val.jsonl \
--model_name answerdotai/ModernBERT-base \
--output_dir ./snes_model \
--epochs 3 --lr 2e-5 --batch_size 1 \
--max_length 8192
Evaluate:
snes-eval --model ./snes_model --data data/test.jsonl
Infer:
snes-infer story.txt --threshold 0.35 --output scene_breaks.json
Data Format (.jsonl)
Each record is one story pre-split into paragraphs:
{"story_id": "uuid-1234", "paragraphs": ["Para 1", "Para 2"], "labels": [0, 1]}
Optional keys: soft_labels, meta.
License
MIT
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file snes-0.0.1.tar.gz.
File metadata
- Download URL: snes-0.0.1.tar.gz
- Upload date:
- Size: 10.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
24ebf849d40b50f1bfee4361329d1ee4913fc7b3ff36f6cc27cb3e3733812760
|
|
| MD5 |
22f693016357ed93144b97c794a00cdb
|
|
| BLAKE2b-256 |
37b12a4efb435fa3285c2538257ef9d8291396d5d27d3590a0da1de0e1ca0cfb
|
File details
Details for the file snes-0.0.1-py3-none-any.whl.
File metadata
- Download URL: snes-0.0.1-py3-none-any.whl
- Upload date:
- Size: 11.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
180b7b70b4ea7413b7f2f25f600e105bd064889001a7b36cd0bc966999e71673
|
|
| MD5 |
71731040fec35d384c6aa76e71169135
|
|
| BLAKE2b-256 |
9f5f5bbdfcd5400298f9d233a4baa5bb6129464ac5a7834d7d59359dbe529b0d
|