Tag: LLM inference
Distributed Transformer Inference: Master Tensor and Pipeline Parallelism for LLMs
Learn how to scale LLMs using Tensor and Pipeline Parallelism. Discover how vLLM and llm-d overcome memory limits to run massive models across multiple GPUs.
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Constrained Decoding for LLMs: Mastering JSON, Regex, and Schema Control
Learn how constrained decoding ensures LLMs produce perfect JSON, regex, and schema-compliant outputs, eliminating syntax errors in production AI pipelines.
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Speculative Decoding with Compressed Draft Models for LLMs: Faster Inference Without Losing Quality
Speculative decoding with compressed draft models cuts LLM inference time by up to 3x by letting a small model predict tokens ahead, while the large model verifies them in parallel. No quality loss-just faster responses.
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