Description
Pretrained VIT model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.image_classifier_vit_Test_Model
is a English model originally trained by Nonem100.
Predicted Entities
nachos
, popcorn
, cotton candy
, hot dog
, hamburger
How to use
pipeline = PretrainedPipeline('pipeline_image_classifier_vit_Test_Model', lang = 'en')
annotations = pipeline.transform(imageDF)
val pipeline = new PretrainedPipeline("pipeline_image_classifier_vit_Test_Model", lang = "en")
val annotations = pipeline.transform(imageDF)
Model Information
Model Name: | pipeline_image_classifier_vit_Test_Model |
Type: | pipeline |
Compatibility: | Spark NLP 4.2.1+ |
License: | Open Source |
Edition: | Official |
Language: | en |
Size: | 321.9 MB |
Included Models
- ImageAssembler
- ViTForImageClassification