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@@ -51,7 +51,7 @@ Here is where Artificial Intelligence 🤖 comes in. Currently, classical machin
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  This model uses [KBIR](https://huggingface.co/bloomberg/KBIR) as its base model and fine-tunes it on the [Inspec dataset](https://huggingface.co/datasets/midas/inspec). KBIR or Keyphrase Boundary Infilling with Replacement is a pre-trained model which utilizes a multi-task learning setup for optimizing a combined loss of Masked Language Modeling (MLM), Keyphrase Boundary Infilling (KBI) and Keyphrase Replacement Classification (KRC).
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  You can find more information about the architecture in this [paper](https://arxiv.org/abs/2112.08547).
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- The model is fine-tuned as a token classification problem where the text is labeled using the BIO scheme.
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  | Label | Description |
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  This model uses [KBIR](https://huggingface.co/bloomberg/KBIR) as its base model and fine-tunes it on the [Inspec dataset](https://huggingface.co/datasets/midas/inspec). KBIR or Keyphrase Boundary Infilling with Replacement is a pre-trained model which utilizes a multi-task learning setup for optimizing a combined loss of Masked Language Modeling (MLM), Keyphrase Boundary Infilling (KBI) and Keyphrase Replacement Classification (KRC).
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  You can find more information about the architecture in this [paper](https://arxiv.org/abs/2112.08547).
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+ Keyphrase extraction models are transformer models fine-tuned as a token classification problem where each word in the document is classified as being part of a keyphrase or not.
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  | Label | Description |
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