Description
Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.emp_legal_deberta_reward_single_rule_words_pipeline is a English model originally trained by cheonkamjeong.
How to use
pipeline = PretrainedPipeline("emp_legal_deberta_reward_single_rule_words_pipeline", lang = "en")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("emp_legal_deberta_reward_single_rule_words_pipeline", lang = "en")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | emp_legal_deberta_reward_single_rule_words_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.1+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 555.5 MB |
References
https://huggingface.co/cheonkamjeong/emp-legal-deberta-reward-single_rule-words
Included Models
- DocumentAssembler
- TokenizerModel
- DeBertaForSequenceClassification