Description
Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.xlm_roberta_qa_afriberta_base_finetuned_tydiqa_pipeline is a Swahili (macrolanguage) model originally trained by cjrowe.
How to use
pipeline = PretrainedPipeline("xlm_roberta_qa_afriberta_base_finetuned_tydiqa_pipeline", lang = "sw")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("xlm_roberta_qa_afriberta_base_finetuned_tydiqa_pipeline", lang = "sw")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | xlm_roberta_qa_afriberta_base_finetuned_tydiqa_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | sw |
| Size: | 415.2 MB |
References
https://huggingface.co/cjrowe/afriberta_base-finetuned-tydiqa
Included Models
- MultiDocumentAssembler
- XlmRoBertaForQuestionAnswering