The rise of large language models (LLMs) has driven significant demand for efficient inference and fine-tuning frameworks. One such framework, vLLM, is optimised for high-performance serving with PagedAttention, allowing for memory-efficient execution across diverse hardware architectures. With the introduction of new AI accelerators such as Gaudi3, H200, and MI300X, optimising fine-tuning parameters is essential to […]
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Simon Todd
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