Description
Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.roberta_base_unlabeled_gab_semeval2023_task10_45000samplesample_pipeline is a English model originally trained by HPL.
How to use
pipeline = PretrainedPipeline("roberta_base_unlabeled_gab_semeval2023_task10_45000samplesample_pipeline", lang = "en")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("roberta_base_unlabeled_gab_semeval2023_task10_45000samplesample_pipeline", lang = "en")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | roberta_base_unlabeled_gab_semeval2023_task10_45000samplesample_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 465.9 MB |
References
https://huggingface.co/HPL/roberta-base-unlabeled-gab-semeval2023-task10-45000samplesample
Included Models
- DocumentAssembler
- TokenizerModel
- RoBertaEmbeddings