Description
Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.tiny_random_distilbertfortokenclassification_hf_internal_testing
is a English model originally trained by hf-internal-testing.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("documents")
tokenClassifier = DistilBertForTokenClassification.pretrained("tiny_random_distilbertfortokenclassification_hf_internal_testing","en") \
.setInputCols(["documents","token"]) \
.setOutputCol("ner")
pipeline = Pipeline().setStages([documentAssembler, tokenClassifier])
pipelineModel = pipeline.fit(data)
pipelineDF = pipelineModel.transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("embeddings")
val tokenClassifier = DistilBertForTokenClassification
.pretrained("tiny_random_distilbertfortokenclassification_hf_internal_testing", "en")
.setInputCols(Array("documents","token"))
.setOutputCol("ner")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenClassifier))
val pipelineModel = pipeline.fit(data)
val pipelineDF = pipelineModel.transform(data)
Model Information
Model Name: | tiny_random_distilbertfortokenclassification_hf_internal_testing |
Compatibility: | Spark NLP 5.2.0+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [documents, token] |
Output Labels: | [ner] |
Language: | en |
Size: | 347.3 KB |
References
https://huggingface.co/hf-internal-testing/tiny-random-DistilBertForTokenClassification