Google BigBird is a transformer-based model designed for natural language processing tasks, capable of handling long sequences of text efficiently by using sparse attention mechanisms, which reduces computational complexity and memory usage.
Top 5*
Large Language Models (LLMs)
About Google BigBird
Google BigBird was introduced in 2020 by researchers at Google AI. It was developed to address limitations in processing long sequences of text in natural language processing tasks, utilizing sparse attention mechanisms to improve efficiency and scalability.
Google BigBird's strengths include efficient handling of long text sequences and reduced computational complexity. Its weaknesses involve potential challenges in sparse attention implementation and limited adoption compared to more established models. Competitors include OpenAI's GPT-3, Facebook's Longformer, and other transformer-based models optimized for long text processing.
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How to hire a Google BigBird expert
A Google BigBird expert must have strong skills in natural language processing, proficiency in Python, experience with transformer architectures, familiarity with TensorFlow or PyTorch, and expertise in sparse attention mechanisms and handling large-scale datasets.
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USA
$ 224K
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$ 127K
Employer Cost
$ 97K
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