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@@ -14,7 +14,7 @@ You can use the raw model for masked language modeling, but it's mostly intended
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  Note that this model is primarily aimed at being fine-tuned on tasks such as visuo-linguistic sequence classification or visual question answering. We used this model to fine-tuned on a multi-translated version of the visual question answering task - [VQA v2](https://visualqa.org/challenge.html). Since Conceptual-12M is a dataset scraped from the internet, it will involve some biases which will also affect all fine-tuned versions of this model.
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  ### How to use❓
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- You can use this model directly with a pipeline for masked language modeling:
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  ```python
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  >>> from torchvision.io import read_image
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  >>> import numpy as np
 
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  Note that this model is primarily aimed at being fine-tuned on tasks such as visuo-linguistic sequence classification or visual question answering. We used this model to fine-tuned on a multi-translated version of the visual question answering task - [VQA v2](https://visualqa.org/challenge.html). Since Conceptual-12M is a dataset scraped from the internet, it will involve some biases which will also affect all fine-tuned versions of this model.
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  ### How to use❓
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+ You can use this model directly with a pipeline for masked language modeling. You will need to clone the model from [here](https://github.com/gchhablani/multilingual-vqa). An example of usage is shown below:
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  ```python
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  >>> from torchvision.io import read_image
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  >>> import numpy as np