Description
Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.ag_nli_bert_mpnet_base_uncased_sentence_similarity_v1_pipeline is a English model originally trained by abbasgolestani.
How to use
pipeline = PretrainedPipeline("ag_nli_bert_mpnet_base_uncased_sentence_similarity_v1_pipeline", lang = "en")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("ag_nli_bert_mpnet_base_uncased_sentence_similarity_v1_pipeline", lang = "en")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | ag_nli_bert_mpnet_base_uncased_sentence_similarity_v1_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 405.5 MB |
References
https://huggingface.co/abbasgolestani/ag-nli-bert-mpnet-base-uncased-sentence-similarity-v1
Included Models
- DocumentAssembler
- MPNetEmbeddings