Description
Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline is a English model originally trained by domenicrosati.
How to use
pipeline = PretrainedPipeline("deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline", lang = "en")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline", lang = "en")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | deberta_embeddings_v3_large_dapt_scientific_papers_pubmed_tapt_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 1.6 GB |
References
https://huggingface.co/domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed-tapt
Included Models
- DocumentAssembler
- TokenizerModel
- DeBertaEmbeddings