quantization-and-model-compression

SKILLFlujo de trabajocomunidad
v0.0.0jpoindexterUnknownActualizado hace 18 dFuente →

Reference-grade guide to shrinking and speeding up LLMs without retraining from scratch — numeric formats (FP8/INT8/INT4), PTQ methods (GPTQ, AWQ, SmoothQuant, bitsandbytes NF4, GGUF k-quants), KV-cache quantization, speculative decoding (Medusa/EAGLE/n-gram), and distillation — with concrete number

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hace 18 dÚltima actualización
Skill
Autorjpoindexter
Versión0.0.0
LicenciaUnknown
CategoríaFlujo de trabajo
Formatosskill.md
PromptNo publicado
Compatibilidad
Claude✓ Compatible
Cursor
Copilot
ChatGPT
Gemini
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Reference-grade guide to shrinking and speeding up LLMs without retraining from scratch — numeric formats (FP8/INT8/INT4), PTQ methods (GPTQ, AWQ, SmoothQuant, bitsandbytes NF4, GGUF k-quants), KV-cache quantization, speculative decoding (Medusa/EAGLE/n-gram), and distillation — with concrete numbers, when each fits, and the quality cliffs.

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