Description
Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.mongolian_xlm_roberta_base_named_entity_pipeline is a Mongolian model originally trained by 2rtl3.
How to use
pipeline = PretrainedPipeline("mongolian_xlm_roberta_base_named_entity_pipeline", lang = "mn")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("mongolian_xlm_roberta_base_named_entity_pipeline", lang = "mn")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | mongolian_xlm_roberta_base_named_entity_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | mn |
| Size: | 842.2 MB |
References
https://huggingface.co/2rtl3/mn-xlm-roberta-base-named-entity
Included Models
- DocumentAssembler
- TokenizerModel
- XlmRoBertaForTokenClassification