Description
Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.sent_bert_base_cased_swe_historical_pipeline is a Swedish model originally trained by Riksarkivet.
How to use
pipeline = PretrainedPipeline("sent_bert_base_cased_swe_historical_pipeline", lang = "sv")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("sent_bert_base_cased_swe_historical_pipeline", lang = "sv")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | sent_bert_base_cased_swe_historical_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | sv |
| Size: | 505.4 MB |
References
https://huggingface.co/Riksarkivet/bert-base-cased-swe-historical
Included Models
- DocumentAssembler
- TokenizerModel
- SentenceDetectorDLModel
- BertSentenceEmbeddings