Description
Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_a_pipeline is a Multilingual model originally trained by haryoaw.
How to use
pipeline = PretrainedPipeline("scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_a_pipeline", lang = "xx")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_a_pipeline", lang = "xx")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_a_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | xx |
| Size: | 836.9 MB |
References
https://huggingface.co/haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all_a
Included Models
- DocumentAssembler
- TokenizerModel
- XlmRoBertaForSequenceClassification