mim-solutions/bert_for_longer_texts

BERT classification model for processing texts longer than 512 tokens. Text is first divided into smaller chunks and after feeding them to BERT, intermediate results are pooled. The implementation allows fine-tuning.

146 33 +0/wk

GitHub

bert deep-learning machine-learning natural-language-processing nlp pytorch roberta text-classification transfer-learning transformers

Trend 0

Star & Fork Trend (18 data points)

Stars

Forks

Multi-Source Signals

GitHub

stars 146

forks 33

Growth Velocity

mim-solutions/bert_for_longer_texts has +0 stars this period . Velocity data will be available after more historical data is collected.

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Metric	bert_for_longer_texts	Sentiment_Analysis_Imdb	tpp-mlir	bidd-molmap
Stars	146	146	147	145
Forks	33	17	38	34
Weekly Growth	+0	+0	+0	+0
Language	Python	Python	MLIR	Jupyter Notebook
Sources	1	1	1	1
License	NOASSERTION	N/A	NOASSERTION	NOASSERTION

Capability Radar vs Sentiment_Analysis_Imdb

bert_for_longer_texts

Sentiment_Analysis_Imdb

Maintenance Activity 0

Last code push 658 days ago.

Community Engagement 100

Fork-to-star ratio: 22.6%. 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 30

No clear license detected — proceed with caution.

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