Discover the architectural design behind BLOOM, the powerful multilingual AI model. Learn how the decoder architecture enables BLOOM to generate coherent text across multiple languages.
Table of Contents
Question
What is the underlying architecture used to design the multilingual AI model, BLOOM?
A. Seq2seq
B. Encoder
C. Encoder-Decoder
D. Decoder
Answer
D. Decoder
Explanation
The underlying architecture used to design the multilingual AI model BLOOM is the Decoder architecture.
BLOOM (BigScience Large Open-science Open-access Multilingual Language Model) is an autoregressive language model, which means it predicts the next word in a sequence based on the previous words. The Decoder architecture is well-suited for this task as it focuses on generating output sequences based on the input context.
In the Decoder architecture, the model takes in the previous words as input and generates the next word in the sequence. This process is repeated iteratively, with the generated word being added to the input for the next step, until a stopping criterion is met (e.g., reaching a maximum sequence length or encountering an end-of-sequence token).
The Decoder architecture used in BLOOM consists of multiple layers of transformer blocks. Each transformer block contains self-attention mechanisms that allow the model to weigh the importance of different words in the input sequence when generating the next word. This enables BLOOM to capture long-range dependencies and generate coherent text.
By using the Decoder architecture, BLOOM can effectively model the probability distribution over the next word given the previous words in the sequence. This architecture choice, combined with the model’s large size and training on a diverse multilingual dataset, allows BLOOM to generate high-quality text in multiple languages.
In summary, the Decoder architecture provides BLOOM with the necessary components to generate contextually relevant and coherent text across multiple languages, making it a powerful tool for various natural language processing tasks.
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