Description
Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.sent_bert_base_uncased_swahili_pipeline is a Swahili (macrolanguage) model originally trained by flax-community.
How to use
pipeline = PretrainedPipeline("sent_bert_base_uncased_swahili_pipeline", lang = "sw")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("sent_bert_base_uncased_swahili_pipeline", lang = "sw")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | sent_bert_base_uncased_swahili_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | sw |
| Size: | 408.6 MB |
References
https://huggingface.co/flax-community/bert-base-uncased-swahili
Included Models
- DocumentAssembler
- TokenizerModel
- SentenceDetectorDLModel
- BertSentenceEmbeddings