Description
Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.sent_alberti_bert_base_multilingual_cased_flax_community_pipeline is a Multilingual model originally trained by flax-community.
How to use
pipeline = PretrainedPipeline("sent_alberti_bert_base_multilingual_cased_flax_community_pipeline", lang = "xx")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("sent_alberti_bert_base_multilingual_cased_flax_community_pipeline", lang = "xx")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | sent_alberti_bert_base_multilingual_cased_flax_community_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | xx |
| Size: | 664.9 MB |
References
https://huggingface.co/flax-community/alberti-bert-base-multilingual-cased
Included Models
- DocumentAssembler
- TokenizerModel
- SentenceDetectorDLModel
- BertSentenceEmbeddings