
# Vision-and-Language Transformer (ViLT), fine-tuned on COCO

Vision-and-Language Transformer (ViLT) model fine-tuned on [COCO](https://cocodataset.org/#home). It was introduced in the paper [ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision](https://arxiv.org/abs/2102.03334) by Kim et al. and first released in [this repository](https://github.com/dandelin/ViLT). 

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

## Intended uses & limitations

You can use the model for image and text retrieval.

### How to use

Here is how to use the model in PyTorch:

```
from transformers import ViltProcessor, ViltForImageAndTextRetrieval
import requests
from PIL import Image

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)
texts = ["An image of two cats chilling on a couch", "A football player scoring a goal"]

processor = ViltProcessor.from_pretrained("dandelin/vilt-b32-finetuned-coco")
model = ViltForImageAndTextRetrieval.from_pretrained("dandelin/vilt-b32-finetuned-coco")

# prepare inputs
encoding = processor(image, text, return_tensors="pt")

# forward pass
scores = dict()
for text in texts:
    encoding = processor(image, text, return_tensors="pt")
    outputs = model(**encoding)
    scores[text] = outputs.logits[0, :].item()
```

## Training data

(to do)

## Training procedure

### Preprocessing

(to do)

### Pretraining

(to do)

## Evaluation results

(to do)

### BibTeX entry and citation info

```bibtex
@misc{kim2021vilt,
      title={ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision}, 
      author={Wonjae Kim and Bokyung Son and Ildoo Kim},
      year={2021},
      eprint={2102.03334},
      archivePrefix={arXiv},
      primaryClass={stat.ML}
}
```
{"license": "apache-2.0"}
transformers pytorch vilt arxiv:2102.03334 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #vilt #arxiv-2102.03334 #license-apache-2.0 #endpoints_compatible #region-us 


# Vision-and-Language Transformer (ViLT), fine-tuned on COCO

Vision-and-Language Transformer (ViLT) model fine-tuned on COCO. It was introduced in the paper ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision by Kim et al. and first released in this repository. 

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

## Intended uses & limitations

You can use the model for image and text retrieval.

### How to use

Here is how to use the model in PyTorch:



## Training data

(to do)

## Training procedure

### Preprocessing

(to do)

### Pretraining

(to do)

## Evaluation results

(to do)

### BibTeX entry and citation info


# Vision-and-Language Transformer (ViLT), fine-tuned on COCO

Vision-and-Language Transformer (ViLT) model fine-tuned on COCO. It was introduced in the paper ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision by Kim et al. and first released in this repository. 

Disclaimer: The team releasing ViLT did not write a model card for this model so this model card has been written by the Hugging Face team. ## Intended uses & limitations

You can use the model for image and text retrieval. ### How to use

Here is how to use the model in PyTorch: ## Training data

(to do) ## Training procedure ### Preprocessing

(to do) ### Pretraining

(to do) ## Evaluation results

(to do) ### BibTeX entry and citation info
TAGS
#transformers #pytorch #vilt #arxiv-2102.03334 #license-apache-2.0 #endpoints_compatible #region-us 
 # Vision-and-Language Transformer (ViLT), fine-tuned on COCO

Vision-and-Language Transformer (ViLT) model fine-tuned on COCO. It was introduced in the paper ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision by Kim et al. and first released in this repository. 

Disclaimer: The team releasing ViLT did not write a model card for this model so this model card has been written by the Hugging Face team. ## Intended uses & limitations

You can use the model for image and text retrieval. ### How to use

Here is how to use the model in PyTorch: ## Training data

(to do) ## Training procedure ### Preprocessing

(to do) ### Pretraining

(to do) ## Evaluation results

(to do) ### BibTeX entry and citation info
passage: TAGS
#transformers #pytorch #vilt #arxiv-2102.03334 #license-apache-2.0 #endpoints_compatible #region-us 
# Vision-and-Language Transformer (ViLT), fine-tuned on COCO

Vision-and-Language Transformer (ViLT) model fine-tuned on COCO. It was introduced in the paper ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision by Kim et al. and first released in this repository. 

Disclaimer: The team releasing ViLT did not write a model card for this model so this model card has been written by the Hugging Face team.## Intended uses & limitations

You can use the model for image and text retrieval.### How to use

Here is how to use the model in PyTorch:## Training data

(to do)## Training procedure### Preprocessing

(to do)### Pretraining

(to do)## Evaluation results

(to do)### BibTeX entry and citation info