Google BARD (Bidirectional Encoder Representations from Transformers with Adapters) is a natural language processing model developed by Google. BARD is a variant of the Transformer model, which is a type of deep learning architecture used in natural language processing.
BARD is designed to be highly adaptable, allowing it to perform well on a variety of natural language processing tasks with minimal task-specific training. It achieves this by using adapters, which are small, task-specific modules that can be plugged into the model to adapt it to a specific task. This approach allows BARD to achieve state-of-the-art results on a wide range of natural language processing tasks with a smaller number of parameters than other models.
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