Reduce model memory by 50-75 percent

Quantize LLMs to 8/4-bit formats for memory reduction

Fitting 7B+ models on consumer GPUs (8-16GB VRAM) when accuracy tolerance permits <1% degradation

• · HuggingFace model path
• · target quantization level (8-bit or 4-bit)
• · BitsAndBytesConfig

• · quantized model in memory
• · device-mapped tensor

• · bitsandbytes
• · transformers
• · accelerate
• · torch

NVIDIA GPU with CUDA; transformers and bitsandbytes installed; sufficient vRAM for loading quantized model

Accuracy degradation at 4-bit; int8_threshold miscalibration causes outlier errors; out-of-memory if vRAM insufficient

• · Supports both INT8 and NF4/FP4 formats per paper
• · QLoRA enables fine-tuning quantized models
• · 50-75% reduction empirically verified