
Separating GGUF Weights, Tokenizer, and Config in vLLM
Distinguish quantized weights, tokenizer, and Hugging Face configuration when starting GGUF models with vLLM.
SignalcraftArticles tagged “vLLM”

Distinguish quantized weights, tokenizer, and Hugging Face configuration when starting GGUF models with vLLM.

Move from guided_json to structured_outputs or response_format while keeping JSON Schema and semantic validation boundaries explicit.

Tune local inference by separating max-model-len, request limits, batching, GPU memory, and reasoning parsers.