yuanxiaosc/BERT-for-Sequence-Labeling-and-Text-Classification

This is the template code to use BERT for sequence lableing and text classification, in order to facilitate BERT for more tasks. Currently, the template code has included conll-2003 named entity identification, Snips Slot Filling and Intent Prediction.

471 96 +0/wk

GitHub

atis-dataset bert conll-2003 sequence-labeling snips-dataset template-project text-classification

Trend 0

Star & Fork Trend (20 data points)

Stars

Forks

Multi-Source Signals

GitHub

stars 471

forks 96

Growth Velocity

yuanxiaosc/BERT-for-Sequence-Labeling-and-Text-Classification has +0 stars this period . Velocity data will be available after more historical data is collected.

Deep analysis is being generated for this repository.

Signal-backed technical analysis will be available soon.

Metric	BERT-for-Sequence-Labeling-and-Text-Classification	vestige	decagon	BERT-for-RRC-ABSA
Stars	471	471	469	465
Forks	96	42	152	111
Weekly Growth	+0	+1	+0	+0
Language	Python	Rust	Jupyter Notebook	Python
Sources	1	1	1	1
License	Apache-2.0	AGPL-3.0	MIT	Apache-2.0

Capability Radar vs vestige

BERT-for-Sequence-Labeling-and-Text-Classification

vestige

Maintenance Activity 0

Last code push 1218 days ago.

Community Engagement 100

Fork-to-star ratio: 20.4%. Active community forking and contributing.

Issue Burden 70

Issue data not yet available.

Growth Momentum 30

No measurable growth in the current period (first-day cold start expected).

License Clarity 95

Licensed under Apache-2.0. Permissive — safe for commercial use.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.