Pierreguillou/Ner Bert Base Cased Pt Lenerbr

What it is

This BERT-based model is designed for named entity recognition (NER) in Portuguese, providing accurate token classification. It's part of the Hugging Face Transformers library and has been widely downloaded and used by developers and researchers.

This model stands out due to its specialized fine-tuning for Portuguese named entity recognition tasks within the BERT architecture, offering high precision and recall rates specifically for the Portuguese language.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Limited language support beyond Portuguese

   The model is specifically fine-tuned for named entity recognition in Portuguese and may not perform well on other languages without significant retraining.

2. 02

   Performance degradation with out-of-domain text

   The model's accuracy drops when processing texts that are significantly different from the training corpus, such as technical or highly informal language.

3. 03

   Resource-intensive inference process

   BERT-based models require substantial computational resources for inference, which can be a bottleneck in real-time applications or on low-power devices.

What it does well

• High accuracy for Portuguese NER tasks

• Based on the BERT architecture, fine-tuned for token classification

• Part of the Hugging Face Transformers library

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.