
# LeViT

LeViT-384 model pre-trained on ImageNet-1k at resolution 224x224. It was introduced in the paper [LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference
](https://arxiv.org/abs/2104.01136) by Graham et al. and first released in [this repository](https://github.com/facebookresearch/LeViT). 

Disclaimer: The team releasing LeViT did not write a model card for this model so this model card has been written by the Hugging Face team.

## Usage

Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes:

```python
from transformers import LevitFeatureExtractor, LevitForImageClassificationWithTeacher
from PIL import Image
import requests

url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
image = Image.open(requests.get(url, stream=True).raw)

feature_extractor = LevitFeatureExtractor.from_pretrained('facebook/levit-384')
model = LevitForImageClassificationWithTeacher.from_pretrained('facebook/levit-384')

inputs = feature_extractor(images=image, return_tensors="pt")
outputs = model(**inputs)
logits = outputs.logits
# model predicts one of the 1000 ImageNet classes
predicted_class_idx = logits.argmax(-1).item()
print("Predicted class:", model.config.id2label[predicted_class_idx])
```
{"license": "apache-2.0", "tags": ["vision", "image-classification"], "datasets": ["imagenet-1k"], "widget": [{"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg", "example_title": "Tiger"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg", "example_title": "Teapot"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg", "example_title": "Palace"}]}
transformers pytorch levit image-classification vision dataset:imagenet-1k arxiv:2104.01136 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #levit #image-classification #vision #dataset-imagenet-1k #arxiv-2104.01136 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


# LeViT

LeViT-384 model pre-trained on ImageNet-1k at resolution 224x224. It was introduced in the paper LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference
 by Graham et al. and first released in this repository. 

Disclaimer: The team releasing LeViT did not write a model card for this model so this model card has been written by the Hugging Face team.

## Usage

Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes:


# LeViT

LeViT-384 model pre-trained on ImageNet-1k at resolution 224x224. It was introduced in the paper LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference
 by Graham et al. and first released in this repository. 

Disclaimer: The team releasing LeViT did not write a model card for this model so this model card has been written by the Hugging Face team. ## Usage

Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes:
TAGS
#transformers #pytorch #levit #image-classification #vision #dataset-imagenet-1k #arxiv-2104.01136 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # LeViT

LeViT-384 model pre-trained on ImageNet-1k at resolution 224x224. It was introduced in the paper LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference
 by Graham et al. and first released in this repository. 

Disclaimer: The team releasing LeViT did not write a model card for this model so this model card has been written by the Hugging Face team. ## Usage

Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes:
passage: TAGS
#transformers #pytorch #levit #image-classification #vision #dataset-imagenet-1k #arxiv-2104.01136 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# LeViT

LeViT-384 model pre-trained on ImageNet-1k at resolution 224x224. It was introduced in the paper LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference
 by Graham et al. and first released in this repository. 

Disclaimer: The team releasing LeViT did not write a model card for this model so this model card has been written by the Hugging Face team.## Usage

Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes: