Description
Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.roberta_model_usefulness_facts_multilable_1_pipeline is a English model originally trained by Spyphy.
How to use
pipeline = PretrainedPipeline("roberta_model_usefulness_facts_multilable_1_pipeline", lang = "en")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("roberta_model_usefulness_facts_multilable_1_pipeline", lang = "en")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | roberta_model_usefulness_facts_multilable_1_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.1+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 438.3 MB |
References
https://huggingface.co/Spyphy/roberta-model-usefulness-facts-multilable-1
Included Models
- DocumentAssembler
- TokenizerModel
- RoBertaForSequenceClassification