Description
Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.summarization_sft_reward_model_deberta_v3_large_v2_pipeline is a English model originally trained by weepcat.
How to use
pipeline = PretrainedPipeline("summarization_sft_reward_model_deberta_v3_large_v2_pipeline", lang = "en")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("summarization_sft_reward_model_deberta_v3_large_v2_pipeline", lang = "en")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | summarization_sft_reward_model_deberta_v3_large_v2_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.1+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 832.6 MB |
References
https://huggingface.co/weepcat/summarization_sft_reward-model-deberta-v3-large-v2
Included Models
- DocumentAssembler
- TokenizerModel
- DeBertaForSequenceClassification