Downloads · 30 days
7
5% of all-time downloads
vit_base_patch16_384_imagenet
keras/vit_base_patch16_384_imagenet
vit_base_patch16_384_imagenet is a machine learning model from keras. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for keras-hub.
Vision Transformer (ViT) adapts the Transformer architecture, originally designed for natural language processing, to the domain of computer vision. It treats images as sequences of patches, similar to how Transformer…
All-time downloads
153
Public
Repo size
2.1 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.h5693 MB · 100%
At a glance
- Library
- keras-hub
- Access
- Public
- Created
- Dec 23, 2024
- Updated
- May 15, 2026
- SHA
- fdc573f0
Model card
From the Hugging Face model README
Model Overview
Model Summary
Vision Transformer (ViT) adapts the Transformer architecture, originally designed for natural language processing, to the domain of computer vision. It treats images as sequences of patches, similar to how Transformers treat sentences as sequences of words.. It was introduced in the paper An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
Links:
- Vit Quickstart Notebook
- Vit API Documentation
- Vit Model Card
- KerasHub Beginner Guide
- KerasHub Model Publishing Guide
Installation
Keras and KerasHub can be installed with:
pip install -U -q keras-hub
pip install -U -q keras
Presets
| Model ID | img_size | Acc | Top-5 | Parameters |
|---|---|---|---|---|
| Base | ||||
| vit_base_patch16_224_imagenet | 224 | - | - | 85798656 |
| vit_base_patch_16_224_imagenet21k | 224 | - | - | 85798656 |
| vit_base_patch_16_384_imagenet | 384 | - | - | 86090496 |
| vit_base_patch32_224_imagenet21k | 224 | - | - | 87455232 |
| vit_base_patch32_384_imagenet | 384 | - | - | 87528192 |
| Large | ||||
| vit_large_patch16_224_imagenet | 224 | - | - | 303301632 |
| vit_large_patch16_224_imagenet21k | 224 | - | - | 303301632 |
| vit_large_patch16_384_imagenet | 224 | - | - | 303690752 |
| vit_large_patch32_224_imagenet21k | 224 | - | - | 305510400 |
| vit_large_patch32_384_imagenet | 224 | - | - | 305607680 |
| Huge | ||||
| vit_huge_patch14_224_imagenet21k | 224 | - | - | 630764800 |
Example Usage
Pretrained ViT model
image_classifier = keras_hub.models.ImageClassification.from_preset(
"vit_base_patch16_384_imagenet"
)
input_data = np.random.uniform(0, 1, size=(2, 224, 224, 3))
image_classifier(input_data)
Load the backbone weights and fine-tune model for custom dataset.
backbone = keras_hub.models.Backbone.from_preset(
"vit_base_patch16_384_imagenet"
)
preprocessor = keras_hub.models.ViTImageClassifierPreprocessor.from_preset(
"vit_base_patch16_384_imagenet"
)
model = keras_hub.models.ViTImageClassifier(
backbone=backbone,
num_classes=len(CLASSES),
preprocessor=preprocessor,
)
Example Usage with Hugging Face URI
Pretrained ViT model
image_classifier = keras_hub.models.ImageClassification.from_preset(
"hf://keras/vit_base_patch16_384_imagenet"
)
input_data = np.random.uniform(0, 1, size=(2, 224, 224, 3))
image_classifier(input_data)
Load the backbone weights and fine-tune model for custom dataset.
backbone = keras_hub.models.Backbone.from_preset(
"hf://keras/vit_base_patch16_384_imagenet"
)
preprocessor = keras_hub.models.ViTImageClassifierPreprocessor.from_preset(
"hf://keras/vit_base_patch16_384_imagenet"
)
model = keras_hub.models.ViTImageClassifier(
backbone=backbone,
num_classes=len(CLASSES),
preprocessor=preprocessor,
)
- Library
- keras-hub
- Created
- Dec 23, 2024
- Updated
- May 15, 2026