Description
Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.twitter_data_bert_base_multilingual_uncased_hindi_only_memes_pipeline is a Multilingual model originally trained by SiddharthaM.
How to use
pipeline = PretrainedPipeline("twitter_data_bert_base_multilingual_uncased_hindi_only_memes_pipeline", lang = "xx")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("twitter_data_bert_base_multilingual_uncased_hindi_only_memes_pipeline", lang = "xx")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | twitter_data_bert_base_multilingual_uncased_hindi_only_memes_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | xx |
| Size: | 627.8 MB |
References
https://huggingface.co/SiddharthaM/twitter-data-bert-base-multilingual-uncased-hindi-only-memes
Included Models
- DocumentAssembler
- TokenizerModel
- BertForSequenceClassification