Write code to quantize activations in a Transformer architecture using QLoRA

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Can you Write code to quantize activations in a Transformer architecture using QLoRA.
Apr 7 in Generative AI by Ashutosh
• 27,850 points
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1 answer to this question.

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You can quantize activations in a Transformer using QLoRA by enabling bnb_4bit_use_double_quant and setting quantization parameters during model loading.

Here is the code snippet you can refer to:

In the above code we are using the following key strategies:

  • Enables double quantization for activation compression.

  • Uses NF4 (normal float 4-bit) for better activation representation.

  • Specifies target modules for fine-grained QLoRA insertion.

  • Compatible with Hugging Face + bitsandbytes quantization backend.

Hence, activation quantization in QLoRA is achieved by configuring quantization-aware loading parameters that efficiently compress intermediate representations in Transformers.
answered Apr 14 by anonymous
• 27,850 points

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