Description
Pretrained Bert Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. sikuroberta is a Chinese model orginally trained by SIKU-BERT.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
embeddings = BertEmbeddings.pretrained("bert_embeddings_sikuroberta","zh") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text")
result = pipeline.fit(data).transform(data)
Model Information
| Model Name: | bert_embeddings_sikuroberta |
| Compatibility: | Spark NLP 3.4.2+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence, token] |
| Output Labels: | [bert] |
| Language: | zh |
| Size: | 408.8 MB |
| Case sensitive: | true |
References
- https://huggingface.co/SIKU-BERT/sikuroberta
- https://github.com/SIKU-BERT/SikuBERT-for-digital-humanities-and-classical-Chinese-information-processing