Datasets:

malaiwah
/

qfs-microfloat-tiny-cpu-format-v1

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[ "pre-seal" ]	[]	1	df49786fa6ab7b99b4ccb964492beb1dfda015c837b9483c9f730bf69e82513c	malaiwah.fidelity-structural-validation.v1	sealed	dataset:fidelity--quant-integration.candidate	[]
[ "pre-seal" ]	[]	1	e119c65652612ff67b867992ad3c228bc641ef07313779c4f7fb572e2d4603f4	malaiwah.fidelity-structural-validation.v1	sealed	dataset:fidelity--quant-integration.root	[]
[ "pre-seal" ]	[]	1	df49786fa6ab7b99b4ccb964492beb1dfda015c837b9483c9f730bf69e82513c	malaiwah.fidelity-structural-validation.v1	sealed	dataset:fidelity--quant-integration.candidate	[]
[ "pre-seal" ]	[]	1	e119c65652612ff67b867992ad3c228bc641ef07313779c4f7fb572e2d4603f4	malaiwah.fidelity-structural-validation.v1	sealed	dataset:fidelity--quant-integration.root	[]
[ "pre-seal" ]	[]	1	df49786fa6ab7b99b4ccb964492beb1dfda015c837b9483c9f730bf69e82513c	malaiwah.fidelity-structural-validation.v1	sealed	dataset:fidelity--quant-integration.candidate	[]
[ "pre-seal" ]	[]	1	e119c65652612ff67b867992ad3c228bc641ef07313779c4f7fb572e2d4603f4	malaiwah.fidelity-structural-validation.v1	sealed	dataset:fidelity--quant-integration.root	[]
[ "pre-seal" ]	[]	1	df49786fa6ab7b99b4ccb964492beb1dfda015c837b9483c9f730bf69e82513c	malaiwah.fidelity-structural-validation.v1	sealed	dataset:fidelity--quant-integration.candidate	[]
[ "pre-seal" ]	[]	1	e119c65652612ff67b867992ad3c228bc641ef07313779c4f7fb572e2d4603f4	malaiwah.fidelity-structural-validation.v1	sealed	dataset:fidelity--quant-integration.root	[]
[ "pre-seal" ]	[]	1	df49786fa6ab7b99b4ccb964492beb1dfda015c837b9483c9f730bf69e82513c	malaiwah.fidelity-structural-validation.v1	sealed	dataset:fidelity--quant-integration.candidate	[]
[ "pre-seal" ]	[]	1	e119c65652612ff67b867992ad3c228bc641ef07313779c4f7fb572e2d4603f4	malaiwah.fidelity-structural-validation.v1	sealed	dataset:fidelity--quant-integration.root	[]

microfloat tiny CPU format fixture reproducibility

Complete tiny random FORMAT fixture evidence. Round-to-nearest (RTN) storage/reader exercise only; optimizer-not-run. No GPTQ/AWQ/AutoRound optimization, calibrated ModelOpt/CT/QAT quality, trained-model quality ranking, GPU parity, or native serving-kernel correctness claim.

Reconstructed weights are evaluated by the captured native forward. KL is own-head, full-vocabulary on the recorded panel, not a benchmark of training quality. Advisory reconstruction and activation omissions are retained verbatim in the raw evidence.

This is a dataset evidence bundle, not a multi-model model repository. Each consumer model has its own repository:

Raw model/source trees, original cards/licenses, captures, reports and retained scripts are preserved under raw/. qualification.json records checked results, source-inventory.json records every original source byte, and publication-plan.json records the exact commands and provenance. Each upstream source retains its own license; the dataset license does not relicense bundled code or checkpoints.

Reproduction commands and source hashes

Commands below are recorded argv, not executed by this publisher. Restore each recorded input from the dataset raw trees and map original absolute paths to your workspace. Retained tools/dependency files and byte hashes are in source-inventory.json; do not substitute moving upstream branches.

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      "333b063b8f4cac60c9ee62a8a4cc5913dbdb3c7e3055680dcc3fa7bc5c208d69",
      "--panel-tokenizer-root",
      "/tmp/qfs-complete-tiny-fixture/model",
      "--lane",
      "other",
      "--device",
      "cpu",
      "--dtype",
      "bfloat16",
      "--author",
      "malaiwah",
      "--schedule",
      "layer-outer",
      "--layer-residency",
      "stream",
      "--disclosures",
      "[{\"code\": \"rtn_format_fixture\", \"severity\": \"info\", \"affects_comparability\": false, \"detail\": \"Local RTN-format fixture; optimizer-not-run; no model-quality or serving-kernel equivalence claim.\"}]",
      "--model",
      "/tmp/qfs-complete-tiny-fixture/model",
      "--out",
      "/tmp/qfs-quant-microfloat-release/proof-public/modelopt-mixed/root",
      "--dataset-id",
      "fidelity--quant-integration.root",
      "--dataset-name",
      "Local quant integration root",
      "--role",
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    "argv": [
      "/tmp/qfs-quant-venv/bin/python",
      "-c",
      "import runpy,sys,torch; torch.set_num_threads(2); torch.set_num_interop_threads(2); p=sys.argv.pop(1); sys.path.insert(0,str(__import__('pathlib').Path(p).parent)); sys.argv[0]=p; runpy.run_path(p,run_name='__main__')",
      "/tmp/qfs-explorer-development/engines/tools/hf_capture.py",
      "--panel",
      "/tmp/qfs-complete-tiny-fixture/panel",
      "--panel-role",
      "final",
      "--panel-binding",
      "/tmp/qfs-quant-microfloat-release/proof-public/modelopt-mixed/panel-binding.json",
      "--panel-binding-sha256",
      "333b063b8f4cac60c9ee62a8a4cc5913dbdb3c7e3055680dcc3fa7bc5c208d69",
      "--panel-tokenizer-root",
      "/tmp/qfs-complete-tiny-fixture/model",
      "--lane",
      "other",
      "--device",
      "cpu",
      "--dtype",
      "bfloat16",
      "--author",
      "malaiwah",
      "--schedule",
      "layer-outer",
      "--layer-residency",
      "stream",
      "--disclosures",
      "[{\"code\": \"rtn_format_fixture\", \"severity\": \"info\", \"affects_comparability\": false, \"detail\": \"Local RTN-format fixture; optimizer-not-run; no model-quality or serving-kernel equivalence claim.\"}]",
      "--model",
      "/tmp/qfs-quant-microfloat-release/stage-main/modelopt-mixed",
      "--out",
      "/tmp/qfs-quant-microfloat-release/proof-public/modelopt-mixed/candidate",
      "--dataset-id",
      "fidelity--quant-integration.candidate",
      "--dataset-name",
      "Local quant integration candidate",
      "--role",
      "quant",
      "--codec",
      "mixed",
      "--declared-bits",
      "4.0",
      "--scope-file",
      "/tmp/qfs-quant-microfloat-release/stage-main/modelopt-mixed/scope.json"
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  },
  {
    "cwd": "/tmp/qfs-explorer-development",
    "argv": [
      "/tmp/qfs-quant-venv/bin/python",
      "-c",
      "import runpy,sys,torch; torch.set_num_threads(2); torch.set_num_interop_threads(2); p=sys.argv.pop(1); sys.path.insert(0,str(__import__('pathlib').Path(p).parent)); sys.argv[0]=p; runpy.run_path(p,run_name='__main__')",
      "/tmp/qfs-explorer-development/bin/fidelity_dataset.py",
      "compare",
      "--reference",
      "/tmp/qfs-quant-microfloat-release/proof-public/modelopt-mixed/root",
      "--candidate",
      "/tmp/qfs-quant-microfloat-release/proof-public/modelopt-mixed/candidate",
      "--out",
      "/tmp/qfs-quant-microfloat-release/proof-public/modelopt-mixed/comparison",
      "--force-compute",
      "--device",
      "cpu",
      "--replay-device",
      "numpy",
      "--replay-dtype",
      "float32",
      "--verify-tensors",
      "--own-heads"
    ]
  }
]

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