Description
Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.xlm_roberta_base_kyrgyzner_the_cramer_project_pipeline is a Kirghiz, Kyrgyz model originally trained by the-cramer-project.
How to use
pipeline = PretrainedPipeline("xlm_roberta_base_kyrgyzner_the_cramer_project_pipeline", lang = "ky")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("xlm_roberta_base_kyrgyzner_the_cramer_project_pipeline", lang = "ky")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | xlm_roberta_base_kyrgyzner_the_cramer_project_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | ky |
| Size: | 777.2 MB |
References
https://huggingface.co/the-cramer-project/xlm-roberta-base-kyrgyzNER
Included Models
- DocumentAssembler
- TokenizerModel
- XlmRoBertaForTokenClassification