Description
Pretrained VIT  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.image_classifier_vit_baseball_stadium_foods is a English model originally trained by nateraw.
Predicted Entities
nachos, popcorn, cotton candy, hot dog, hamburger
How to use
    pipeline = PretrainedPipeline('pipeline_image_classifier_vit_baseball_stadium_foods', lang = 'en')
    annotations =  pipeline.transform(imageDF)
    
    val pipeline = new PretrainedPipeline("pipeline_image_classifier_vit_baseball_stadium_foods", lang = "en")
    val annotations = pipeline.transform(imageDF)
    
Model Information
| Model Name: | pipeline_image_classifier_vit_baseball_stadium_foods | 
| Type: | pipeline | 
| Compatibility: | Spark NLP 4.2.1+ | 
| License: | Open Source | 
| Edition: | Official | 
| Language: | en | 
| Size: | 321.9 MB | 
Included Models
- ImageAssembler
- ViTForImageClassification