Italian BertForMaskedLM Base Cased model (from Geotrend)

Description

Pretrained BertForMaskedLM model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bert-base-it-cased is a Italian model originally trained by Geotrend.

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How to use

documentAssembler = DocumentAssembler() \
    .setInputCol("text") \
    .setOutputCol("document")

tokenizer = Tokenizer() \
    .setInputCols("document") \
    .setOutputCol("token")

bert_loaded = BertEmbeddings.pretrained("bert_embeddings_base_it_cased","it") \
    .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_it_cased","it")
    .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("it.embed.bert.cased_base").predict("""I love Spark NLP""")

Model Information

Model Name:	bert_embeddings_base_it_cased
Compatibility:	Spark NLP 4.2.4+
License:	Open Source
Edition:	Official
Input Labels:	[sentence, token]
Output Labels:	[bert]
Language:	it
Size:	396.5 MB
Case sensitive:	true

References

https://huggingface.co/Geotrend/bert-base-it-cased
https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf
https://github.com/Geotrend-research/smaller-transformers

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