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meta-llama/Llama-3.2-3B-Instruct at source revision 0cb88a4f764b7a12671c53f0838cd831a0843b95. It remains subject to the base model's license, intended use, and limitations.| Component | Method | Weight format | Details |
|---|---|---|---|
| Decoder Linear layers | AutoRound | symmetric INT4, G256 | 196 targets; lm_head excluded |
lm_head | GPTQ | symmetric INT4, G256 | static act-order, block size 128, dampening 0.01 |
| Mixed-precision exceptions | — | source dtype | non-Linear parameters remain at source precision |
HuggingFaceH4/ultrachat_200k (dataset revision not captured), train_sft[:512], rendered with the source chat template. Token IDs were deterministically concatenated and packed into 512 full 1024-token spans (no shuffle); AutoRound used 200 iterations and batch size 1.wikitext-2-raw-v1 evaluation used the wikitext lm-eval task, no example limit, batch size 1, CUDA, and the same evaluator for source and quantized checkpoints on 2026-07-19.| Checkpoint | Word perplexity | Status |
|---|---|---|
meta-llama/Llama-3.2-3B-Instruct source | 13.390631 | Full run |
| This UltraChat checkpoint | 21.088042 | Full run |
| Absolute degradation | 7.697411 | Lower is better |
| Relative degradation | 57.484% | 100 * (quantized / source - 1) |
quantize.py, recipe.yaml, and versions.txt.python quantize.py --model-path /path/to/models--meta-llama--Llama-3.2-3B-Instruct --output-dir /path/to/outputversions.txt.