Description
Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.smids_10x_deit_tiny_rms_00001_fold5
is a English model originally trained by hkivancoral.
How to use
image_assembler = ImageAssembler()\
.setInputCol("image")\
.setOutputCol("image_assembler")
imageClassifier = ViTForImageClassification.pretrained(""smids_10x_deit_tiny_rms_00001_fold5","en")\
.setInputCols("image_assembler")\
.setOutputCol("class")
pipeline = Pipeline(stages=[
image_assembler,
imageClassifier,
])
pipelineModel = pipeline.fit(imageDF)
pipelineDF = pipelineModel.transform(imageDF)
val imageAssembler = new ImageAssembler()
.setInputCol("image")
.setOutputCol("image_assembler")
val imageClassifier = ViTForImageClassification.pretrained("smids_10x_deit_tiny_rms_00001_fold5","en")
.setInputCols("image_assembler")
.setOutputCol("class")
val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
val pipelineModel = pipeline.fit(imageDF)
val pipelineDF = pipelineModel.transform(imageDF)
Model Information
Model Name: | smids_10x_deit_tiny_rms_00001_fold5 |
Compatibility: | Spark NLP 5.5.1+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [image_assembler] |
Output Labels: | [label] |
Language: | en |
Size: | 20.8 MB |
References
https://huggingface.co/hkivancoral/smids_10x_deit_tiny_rms_00001_fold5