Description
Pretrained Bert Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. gbert-large
is a German model orginally trained by deepset
.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
embeddings = BertEmbeddings.pretrained("bert_embeddings_gbert_large","de") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
data = spark.createDataFrame([["Ich liebe Funken NLP"]]).toDF("text")
result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val tokenizer = new Tokenizer()
.setInputCols(Array("document"))
.setOutputCol("token")
val embeddings = BertEmbeddings.pretrained("bert_embeddings_gbert_large","de")
.setInputCols(Array("document", "token"))
.setOutputCol("embeddings")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
val data = Seq("Ich liebe Funken NLP").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("de.embed.gbert_large").predict("""Ich liebe Funken NLP""")
Model Information
Model Name: | bert_embeddings_gbert_large |
Compatibility: | Spark NLP 3.4.2+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [sentence, token] |
Output Labels: | [bert] |
Language: | de |
Size: | 1.3 GB |
Case sensitive: | true |
References
- https://huggingface.co/deepset/gbert-large
- https://arxiv.org/pdf/2010.10906.pdf
- https://arxiv.org/pdf/2010.10906.pdf
- https://deepset.ai/german-bert
- https://deepset.ai/germanquad
- https://github.com/deepset-ai/FARM
- https://github.com/deepset-ai/haystack/
- https://twitter.com/deepset_ai
- https://www.linkedin.com/company/deepset-ai/
- https://haystack.deepset.ai/community/join
- https://github.com/deepset-ai/haystack/discussions
- https://deepset.ai
- http://www.deepset.ai/jobs