Description
Pretrained BertForMaskedLM model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bert-base-arabertv02
is a Arabic model originally trained by aubmindlab
.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
bert_loaded = BertEmbeddings.pretrained("bert_embeddings_base_arabertv02","ar") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings") \
.setCaseSensitive(True)
pipeline = Pipeline(stages=[documentAssembler, tokenizer, bert_loaded])
data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text")
result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val tokenizer = new Tokenizer()
.setInputCols("document")
.setOutputCol("token")
val bert_loaded = BertEmbeddings.pretrained("bert_embeddings_base_arabertv02","ar")
.setInputCols(Array("document", "token"))
.setOutputCol("embeddings")
.setCaseSensitive(True)
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, bert_loaded))
val data = Seq("I love Spark NLP").toDS.toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("ar.embed.bert.base.v2.by_aubmindlab").predict("""I love Spark NLP""")
Model Information
Model Name: | bert_embeddings_base_arabertv02 |
Compatibility: | Spark NLP 4.2.4+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [sentence, token] |
Output Labels: | [bert] |
Language: | ar |
Size: | 507.8 MB |
Case sensitive: | true |
References
- https://huggingface.co/aubmindlab/bert-base-arabertv02
- https://github.com/google-research/bert
- https://arxiv.org/abs/2003.00104
- https://github.com/WissamAntoun/pydata_khobar_meetup
- http://alt.qcri.org/farasa/segmenter.html
- /aubmindlab/bert-base-arabertv02/blob/main/(https://github.com/google-research/bert/blob/master/multilingual.md)
- https://github.com/elnagara/HARD-Arabic-Dataset
- https://www.aclweb.org/anthology/D15-1299
- https://staff.aub.edu.lb/~we07/Publications/ArSentD-LEV_Sentiment_Corpus.pdf
- https://github.com/mohamedadaly/LABR
- http://curtis.ml.cmu.edu/w/courses/index.php/ANERcorp
- https://github.com/husseinmozannar/SOQAL
- https://github.com/aub-mind/arabert/blob/master/AraBERT/README.md
- https://arxiv.org/abs/2003.00104v2
- https://archive.org/details/arwiki-20190201
- https://www.semanticscholar.org/paper/1.5-billion-words-Arabic-Corpus-El-Khair/f3eeef4afb81223df96575adadf808fe7fe440b4
- https://www.aclweb.org/anthology/W19-4619
- https://sites.aub.edu.lb/mindlab/
- https://www.yakshof.com/#/
- https://www.behance.net/rahalhabib
- https://www.linkedin.com/in/wissam-antoun-622142b4/
- https://twitter.com/wissam_antoun
- https://github.com/WissamAntoun
- https://www.linkedin.com/in/fadybaly/
- https://twitter.com/fadybaly
- https://github.com/fadybaly