Description
Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.results_pipeline is a Uzbek model originally trained by Xojakbar.
How to use
pipeline = PretrainedPipeline("results_pipeline", lang = "uz")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("results_pipeline", lang = "uz")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | results_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.1+ |
| License: | Open Source |
| Edition: | Official |
| Language: | uz |
| Size: | 819.0 MB |
References
https://huggingface.co/Xojakbar/results
Included Models
- DocumentAssembler
- TokenizerModel
- XlmRoBertaForTokenClassification