Jean Baptiste/Camembert Ner
French Named Entity Recognition model using CamemBERT architecture.
Pricing
See website
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
—Overview
What is Jean Baptiste/Camembert Ner?
This model is designed for token classification tasks, specifically named entity recognition in French text. It leverages the CamemBERT transformer architecture to provide accurate and context-aware entity extraction.
Key differentiator
“Jean-Baptiste/camembert-ner stands out as an open-source, high-performance French named entity recognition model based on CamemBERT, offering developers and researchers a powerful tool for NLP tasks involving the French language.”
Capability profile
Strength Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
Fit analysis
Who is it for?
✓ Best for
Projects requiring high accuracy named entity recognition for French text
Developers working on natural language processing tasks involving the French language
✕ Not a fit for
Applications that require real-time NER with extremely low latency
Tasks where the model needs to be deployed in a fully managed cloud service without self-hosting capabilities
Cost structure
Pricing
Free Tier
None
Starts at
See website
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Next step
Get Started with Jean Baptiste/Camembert Ner
Step-by-step setup guide with code examples and common gotchas.