Dslim/Distilbert NER
DistilBERT model for Named Entity Recognition
Pricing
See website
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
—Overview
What is Dslim/Distilbert NER?
A lightweight DistilBERT model fine-tuned for Named Entity Recognition tasks, offering efficient and accurate entity extraction from text.
Key differentiator
“dslim/distilbert-NER offers an efficient and lightweight solution for Named Entity Recognition, making it ideal for applications with limited computational resources.”
Capability profile
Strength Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
Fit analysis
Who is it for?
✓ Best for
Projects requiring efficient and accurate Named Entity Recognition without heavy computational resources
Developers working on text analysis applications who need a lightweight yet powerful model
✕ Not a fit for
Applications that require real-time entity extraction from extremely large datasets
Scenarios where the use of pre-trained models is not acceptable due to specific domain requirements
Cost structure
Pricing
Free Tier
None
Starts at
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Model
Flat rate
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Performance benchmarks
How Fast Is It?
Ecosystem
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Next step
Get Started with Dslim/Distilbert NER
Step-by-step setup guide with code examples and common gotchas.