How can you build context-aware decoders for generative AI applications

Question

I was facing the issue of building a context-aware decoder for generative AI applications. Can you tell me how you can build context-aware decoders for generative AI applications?

Answer 1

To build context-aware decoders for generative AI, you can use attention mechanisms to incorporate context into the decoding process. Transformers inherently achieve this with self-attention and encoder-decoder attention.

Here is the code snippet below which uses Hugging Face's transformers library with an encoder-decoder model (e.g., BART):

In the above code, we are using the following key techniques:

• Encoder-Decoder Models: Combine encoded context with decoder inputs.
• Attention Mechanisms: Ensure the decoder focuses on relevant parts of the context.
• Beam Search & Temperature: Improve response coherence and relevance.

Hence, by referring to the above, you can build context-aware decoders for generative AI applications.

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