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LinkBERT Large



LinkBERT-large is a model for text classification tasks. It is a large-scale version of the LinkBERT model, which utilizes self-attention mechanisms to process text input. It has been trained on a large corpus of text and can be fine-tuned for specific classification tasks. The model is able to understand the semantic relationships between words and can make accurate predictions for various NLP tasks such as sentiment analysis, topic classification, and spam detection.

Use cases

The LinkBERT-large model has a variety of potential use cases in the field of natural language processing. It can be used for sentiment analysis, helping businesses understand the attitudes and opinions expressed in customer reviews, social media posts, and other forms of text. It can also be used for topic classification, automatically categorizing documents or articles into different topics or themes. Additionally, the model can be applied to spam detection, identifying and filtering out unwanted or malicious content in emails, comments, or messages. Given its ability to understand the semantic relationships between words, LinkBERT-large has the potential to be integrated into a wide range of products and services, such as chatbots, content recommendation systems, and content moderation tools.



Cost per run
Avg run time

Creator Models

Bio Dragon$?0
BioLinkBERT Large$?2,812
LinkBERT Base$?2,065
BioLinkBERT Base$?8,154

Similar Models

Try it!

You can use this area to play around with demo applications that incorporate the LinkBERT Large model. These demos are maintained and hosted externally by third-party creators. If you see an error, message me on Twitter.

Currently, there are no demos available for this model.


Summary of this model and related resources.

Model NameLinkBERT Large
Platform did not provide a description for this model.
Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided


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