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README.md
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license: apache-2.0
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---
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---
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license: apache-2.0
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---
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# Vision-and-Language Transformer (ViLT), fine-tuned on VSR random split
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Vision-and-Language Transformer (ViLT) model fine-tuned on random split of [Visual Spatial Reasoning (VSR)](https://arxiv.org/abs/2205.00363). ViLT was introduced in the paper [ViLT: Vision-and-Language Transformer
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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).
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## Intended uses & limitations
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You can use the model to determine whether a sentence is true or false given an image.
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### How to use
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Here is how to use the model in PyTorch:
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```
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from transformers import ViltProcessor, ViltForImagesAndTextClassification
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import requests
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from PIL import Image
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image = Image.open(requests.get("https://camo.githubusercontent.com/ffcbeada14077b8e6d4b16817c91f78ba50aace210a1e4754418f1413d99797f/687474703a2f2f696d616765732e636f636f646174617365742e6f72672f747261696e323031372f3030303030303038303333362e6a7067", stream=True).raw)
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text = "The person is ahead of the cow."
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processor = ViltProcessor.from_pretrained("juletxara/vilt-vsr-random")
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model = ViltForImagesAndTextClassification.from_pretrained("juletxara/vilt-vsr-random")
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# prepare inputs
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encoding = processor(image, text, return_tensors="pt")
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# forward pass
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outputs = model(input_ids=encoding.input_ids, pixel_values=encoding.pixel_values.unsqueeze(0))
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logits = outputs.logits
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idx = logits.argmax(-1).item()
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print("Predicted answer:", model.config.id2label[idx])
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```
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## Training data
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(to do)
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## Training procedure
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### Preprocessing
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(to do)
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### Pretraining
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(to do)
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## Evaluation results
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(to do)
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### BibTeX entry and citation info
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```bibtex
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@misc{kim2021vilt,
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title={ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision},
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author={Wonjae Kim and Bokyung Son and Ildoo Kim},
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year={2021},
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eprint={2102.03334},
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archivePrefix={arXiv},
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primaryClass={stat.ML}
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}
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@article{liu2022visual,
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title={Visual Spatial Reasoning},
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author={Liu, Fangyu and Emerson, Guy and Collier, Nigel},
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journal={arXiv preprint arXiv:2205.00363},
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year={2022}
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}
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```
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