One row per published run: model identity, contract identifiers, fixture hash, decoding conditions, licence, and the SHA-256 and byte size of both weight artifacts. Accompanied by the calibration lineage that informed each published run.
Part of the quant_eval public corpus: a per-case behavioral evaluation of full-weight and quantized large language models across eight agent-relevant task families, with paired statistical testing.
Cite this dataset:… See the full description on the dataset page:
https://huggingface.co/datasets/pbhappliedsystems/quant_eval_run_provenance.
