GGML and GGUF for Efficient LLM Inference
A practical guide to efficient LLM inference with GGML and GGUF, covering quantization, memory mapping, tokenization, optimization, deployment trade-offs, and local model serving patterns.
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A practical guide to efficient LLM inference with GGML and GGUF, covering quantization, memory mapping, tokenization, optimization, deployment trade-offs, and local model serving patterns.
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This post explores a novel two-stage AI system combining deep learning and large language models to predict and explain shock events in ICU patients, enhancing transparency and trustworthiness in critical care AI.