Meta-Llama-3-8B quantized to 4-bit weights / 16-bit activations, group size 128, with KronQ (Kronecker-factored Hessian quantization). Packed int4 (~5.5 GB); a fused dequant + bidirectional-incoherence (BiIP) CUDA kernel with per-group scales unpacks on the fly.

Results (WikiText-2, seqlen 2048)

Perplexity: 6.337

Zero-shot accuracy:

PIQA	ARC-E	ARC-C	HellaSwag	WinoGrande	BoolQ	OBQA	Average
80.36	78.87	53.24	78.37	73.32	80.92	45.80	70.13

(lm-evaluation-harness 0-shot; acc_norm for PIQA/HellaSwag/ARC, acc for WinoGrande/BoolQ.)

Usage

python eval_pretrained.py meta-llama/Meta-Llama-3-8B donghyunli/Meta-Llama-3-8B-KronQ-W4A16-g128 --ppl --zs

Recipe

Group-128 asymmetric W4, weight-only (a_bits=16), --alpha 0.25, --act_order, BiIP, raw H_G. 128 WikiText-2 calibration sequences.

License

Derivative of Meta-Llama-3-8B — llama3 license.