Description
Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.vit_base_patch16_224_in21k_weather_images_classification_pipeline is a English model originally trained by DunnBC22.
How to use
pipeline = PretrainedPipeline("vit_base_patch16_224_in21k_weather_images_classification_pipeline", lang = "en")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("vit_base_patch16_224_in21k_weather_images_classification_pipeline", lang = "en")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | vit_base_patch16_224_in21k_weather_images_classification_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.1+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 321.4 MB |
References
https://huggingface.co/DunnBC22/vit-base-patch16-224-in21k-weather-images-classification
Included Models
- ImageAssembler
- ViTForImageClassification