MODEL PROFILE

bert-base-swedish-cased

KB · bert-base-swedish-cased

The National Library of Sweden / KBLab releases three pretrained language models based on BERT and ALBERT. The models are trained on aproximately 15-20GB of text (200M sentences, 3000M tokens) from various sources (books, news, government publications, swedish wikipedia and internet forums) aiming to provide a representative BERT model for Swedish text. A more complete description will be published later on. - **bert-base-swedish-cased** (*v1*) - A BERT trained with the same hyperparameters as first published by Google. - **bert-base-swedish-cased-ner** (*experimental*) - a BERT fine-tuned for NER using SUC 3.0. - **albert-base-swedish-cased-alpha** (*alpha*) - A first attempt at an ALBERT for Swedish. The examples below require Huggingface Transformers 2.4.1 and Pytorch 1.3.1 or greater. For Transformers<2.4.0 the tokenizer must be instantiated manually and the `do_lower_case` flag parameter set to `False` and `keep_accents` to `True` (for ALBERT).

Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/30 18:09:05
OVERVIEW

Model overview

The National Library of Sweden / KBLab releases three pretrained language models based on BERT and ALBERT. The models are trained on aproximately 15-20GB of text (200M sentences, 3000M tokens) from various sources (books, news, government publications, swedish wikipedia and internet forums) aiming to provide a representative BERT model for Swedish text. A more complete description will be published later on. - **bert-base-swedish-cased** (*v1*) - A BERT trained with the same hyperparameters as first published by Google. - **bert-base-swedish-cased-ner** (*experimental*) - a BERT fine-tuned for NER using SUC 3.0. - **albert-base-swedish-cased-alpha** (*alpha*) - A first attempt at an ALBERT for Swedish. The examples below require Huggingface Transformers 2.4.1 and Pytorch 1.3.1 or greater. For Transformers<2.4.0 the tokenizer must be instantiated manually and the `do_lower_case` flag parameter set to `False` and `keep_accents` to `True` (for ALBERT).

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

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PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Frequently asked questions

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Sources & traceability

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