evidence: per-window NLLs and diagnostics

README.md

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+---
+license: mit
+pretty_name: "llm-weight-compression evidence"
+language:
+  - en
+tags:
+  - quantization
+  - gptq
+  - post-training-quantization
+  - pre-registered
+  - evaluation
+size_categories:
+  - n<1K
+---
+
+# llm-weight-compression: evidence
+
+Per-window evaluation data and raw diagnostics behind every number in
+[rosecky/llm-weight-compression-public](https://github.com/rosecky/llm-weight-compression-public):
+a pre-registered study of refining GPTQ's integer codes against the output of the enclosing
+attention/MLP module instead of the single layer, on Qwen2.5-0.5B, Qwen3-0.6B,
+Llama-3.2-1B and Qwen2.5-1.5B at exactly 3.25 bits per weight, plus rate–distortion,
+estimation-budget and 2-bit vector-quantized points on Qwen2.5-0.5B.
+
+## Layout
+
+```
+validation/    frozen-protocol runs: one .jsonl per (model, calibration draw) with
+               per-window mean NLL for every arm on the full wikitext-2 test (146 windows
+               of 2048 tokens) and 512 fixed C4 validation windows, plus a summary row per
+               arm (bpw, KL to fp16, objective ratios, flips, timings, peak VRAM); the
+               matching .log is the run's stdout
+diagnostics/   exploratory-phase runs (objective ladder, superadditivity, VQ factorial),
+               probe-budget rescoring, rotation landscape, rate-allocation oracle, oracle
+               prediction features
+box_scripts/   the exact shell scripts run on the rented GPU instance
+README.md      file-by-file map and the pre-registration commit for each stage
+```
+
+Each `validation/*.jsonl` row is either `{"arm", "eval": "wt2"|"c4", "nlls": [...],
+"nll": mean}` or a per-arm summary with `bpw`, `nll_wt2`, `nll_c4`, `kl_fp16`, `obj_ratio`,
+`obj_fresh`, `flips`, `opt_s`, `peak_vram_mib`. Windows are in corpus order, so any two
+arms of the same file are paired window by window.
+
+## Regenerate the tables
+
+```
+git clone https://github.com/rosecky/llm-weight-compression-public
+python scripts/analyze_valid.py --print    # four-model table, paired bootstraps within draw
+python scripts/analyze_rd.py               # rate–distortion, equivalent bits
+python scripts/analyze_d3.py               # halves, calibration domain, estimation budgets
+```
+
+with the analysis scripts pointed at this dataset's `validation/` directory. No GPU is
+needed.
+
+## Provenance
+
+Method and protocol were frozen and committed before any validation run
+(`docs/FROZEN_PROTOCOL.md` in the repository); diagnostic addenda were pre-registered with
+interpretation tables before running. The 2-bit checkpoints evaluated in
+`validation/p4_*` and `validation/d4_*` were produced by a per-block VQ quantiser from the
+embedding-quantization project (d=4, K=256, ~2.1 bpw, input-side rotation) that is not part
+of this release; the dequantised evaluations are.
+
+Author: Jan Rosecký, September 2026. Experiments run with Claude (Anthropic) as an
+autonomous research agent under the author's direction. License: MIT.

evidence/README.md

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+# Evidence
+
+The raw measurements behind every claim in `docs/PITCH.md`, `docs/BRIEFING.md` and
+`docs/FINDINGS.md`. `results/raw/` is scratch and git-ignored; this directory is the
+committed record, because most of it was produced on a rented GPU instance that no longer
+exists.
+
+Regenerate the tables with `python scripts/analyze_valid.py --print` (point `RAW` at
+`evidence/validation`), `python scripts/analyze_rd.py` for the rate–distortion curve, `python scripts/analyze_d3.py`
+for addendum D3, and
+`python scripts/analyze_*.py` for the rest.
+
+## validation/
+
+Frozen-protocol runs (method and hyperparameters committed at `b57c9ac` before any of these
+ran; see `docs/FROZEN_PROTOCOL.md`). These back the four-model headline table.
+
+| file | model | draws | arms |
+|---|---|---|---|
+| `valid_qwen05_s{0,1,2}` | Qwen2.5-0.5B | 3 | fp16, gptq, layer, module, block |
+| `valid_qwen3_06b_s{0,1}` | Qwen3-0.6B | 2 | fp16, gptq, module |
+| `p3_llama1b`, `p3_llama1b_s{1,2}` | Llama-3.2-1B | 3 | fp16, gptq, (layer), module |
+| `valid_qwen15_s{0,1}`, `valid_qwen15_s1b` | Qwen2.5-1.5B | 2 | fp16, gptq, layer, module, block |
+| `rd_q05_b2g64`, `rd_q05_b3g64`, `rd_q05_b4g128` | Qwen2.5-0.5B, draw 0, at 2.50 / 3.50 / 4.25 bpw | 1 | fp16, gptq, module |
+| `p6_llama3b_s0` | Llama-3.2-3B | 1 | fp16, gptq only (module arm lost, see below) |
+| `d3a_qwen05_halves_s0` | Qwen2.5-0.5B, draw 0 | 1 | fp16, module_attn, module_mlp (D3a interaction; local RTX 4050) |
+| `d3c_qwen05_c4calib_s0` | Qwen2.5-0.5B, draw 0, **C4-train calibration** | 1 | fp16, gptq, module (D3c) |
+| `d3b_qwen05_model_{p2_t2k,p8_t2k,p2_t8k}_s0` | Qwen2.5-0.5B, draw 0 | 1 each | fp16, `model` (full-model Fisher) at 2 probes/2k tokens, 8 probes/2k, 2 probes/8k (D3b) |
+| `d3bx_qwen05_attn_t8k_s0` | Qwen2.5-0.5B, draw 0 | 1 | fp16, `module_attn` at 2 probes/8k tokens (D3b-ext; compare `d3a_*` at 2k) |
+| `d3bx2_qwen05_module_t8k_s0` | Qwen2.5-0.5B, draw 0 | 1 | fp16, `module` at 2 probes/8k tokens (D3b-ext2; compare `valid_qwen05_s0` module at 2k — worse) |
+| `p4_qwen05_vq20_{plain,refine}` | Qwen2.5-0.5B, draw 0, **peer's per-block VQ at 2.12 bpw** | 1 each | fp16 + the external checkpoint evaluated as-is (`scripts/eval_external.py`); `refine` = same quantisation + our sequential post-pass (6+6, 8k metric tokens) inside the peer's loop (P4) |
+| `d4_qwen05_vq20_prefix` | same two checkpoints | 1 | both evaluated with a fixed "
+
+" prefix on every window (`scripts/eval_prefix.py`, addendum D4): the first-token tail disappears, refine − plain −0.030 on both sets |
+
+Each `.jsonl` holds one record per (arm, eval set) with **per-window NLLs**, so the paired
+bootstrap is reproducible offline without re-running anything. `valid_qwen15_s1` is the run
+that died in a shared-GPU OOM; `valid_qwen15_s1b` is its completed replacement.
+
+The `rd_*` files are the rate–distortion sweep (P6): the frozen method at three more exact
+rates, evaluated with the same driver (`--bits`/`--group` overrides only). Together with
+`valid_qwen05_s0` (3.25 bpw) they give the four-point curve;
+`python scripts/analyze_rd.py` bootstraps each point. `p6_llama3b_s0` holds the fp16 and
+GPTQ references for Llama-3.2-3B; its module arm was at layer 8/27 after 2.2 h when the
+instance was shut down (`monitor_rd_and_llama3b.log`, `p6_llama3b_s0.log`), so nothing
+above 1.5B is tested. All of these were recovered from the instance disk after a brief
+power-on; `E47` in `EXPERIMENT_LOG.md` records the near-loss.
+
+## diagnostics/
+
+Measurements behind the mechanism claims and the negative results:
+
+- `probe_05b`, `probe_15b`, `noise_probe`, `sweep.log` — rescoring the same weight change
+  under 4×–16× better-estimated metrics. Shows the "improvement" on the widest matrices is
+  illusory **on the model where the method works** as well as where it fails.
+- `d2_*` — the block-diagonal / pre-o_proj endpoint variants that failed on both models.
+- `attn_decomp` — the intra-attention objective ladder and the sensitivity correlations.
+- `joint_ppl` — the exploratory-phase end-to-end runs (radius curve, superadditivity,
+  half-depth split, VQ factorial). Lighter 24-window protocol; not comparable to
+  `validation/`.
+- `rate_alloc` — the rate-allocation oracle that killed that branch (≤0.11 equivalent bpw).
+- `transform_plateau` — tangent, basin, DFO and 200-rotation sweep of the rotation landscape.
+- `gptq_scalefeed` — the scale-source ablation (frozen vs working-weight scales).
+- `oracle_pred` — per-row features vs the CD→exact-search gap, 1440 rows.
+- `calib_size`, `comp_capacity`, `joint_oracle_k` — calibration budget sweep, compensation
+  capacity ladder, and the k-move reconciliation with CDQuant.
+
+## box_scripts/
+
+The exact shell scripts run on the rented instance, kept so the provenance of each result
+file is auditable.

evidence/box_scripts/lwc_d2.sh

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+#!/bin/bash
+cd /root/lwc/repo_new || exit 1
+export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
+export OMP_NUM_THREADS=16
+export PYTHONPATH=src
+P=/venv/main/bin/python
+R=/root/lwc/results
+$P -u -m lwc.experiments.valid_eval --model Qwen/Qwen2.5-1.5B --calib-seed 0 \
+   --fresh-g-seq 16 --arms module_bd --out $R/d2_qwen15_bd.jsonl > $R/d2_qwen15_bd.log 2>&1
+touch $R/D2A_DONE
+$P -u -m lwc.experiments.valid_eval --model Qwen/Qwen2.5-0.5B --calib-seed 0 \
+   --fresh-g-seq 16 --arms module_bd --out $R/d2_qwen05_bd.jsonl > $R/d2_qwen05_bd.log 2>&1
+touch $R/D2B_DONE
+$P -u -m lwc.experiments.valid_eval --model Qwen/Qwen2.5-1.5B --calib-seed 0 \
+   --fresh-g-seq 16 --arms module_pre --out $R/d2_qwen15_pre.jsonl > $R/d2_qwen15_pre.log 2>&1
+touch $R/D2_DONE

evidence/box_scripts/lwc_d3.sh

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+#!/bin/bash
+# D3: maximum-power test of the estimation hypothesis -- BOTH fixes at once.
+# Attention side: exact per-head structure (cheap, already shown to be exact).
+# MLP side: 8x probe budget, the only lever available where no exact structure exists.
+while [ ! -f /root/lwc/results/D2B_DONE ]; do sleep 120; done
+cd /root/lwc/repo_new || exit 1
+export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
+export OMP_NUM_THREADS=16
+export PYTHONPATH=src
+P=/venv/main/bin/python
+R=/root/lwc/results
+$P -u -m lwc.experiments.valid_eval --model Qwen/Qwen2.5-1.5B --calib-seed 0 \
+   --fresh-g-seq 16 --arms module_bd --g-tokens 16384 --n-probe 4 \
+   --out $R/d3_qwen15_bd_hi.jsonl > $R/d3_qwen15_bd_hi.log 2>&1
+touch $R/D3_DONE

evidence/box_scripts/lwc_final.sh

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+#!/bin/bash
+# Overnight: (1) rate-distortion curve on the best-case model, to convert our effect into
+# equivalent bits saved -- the only commercially meaningful unit; (2) Llama-3.2-3B, the
+# largest model we will have tested and the only one above the failure point on a family
+# that works.
+cd /root/lwc/repo_rd || exit 1
+export PYTHONPATH=src OMP_NUM_THREADS=16 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
+P=/venv/main/bin/python
+R=/root/lwc/results
+# (1) R-D curve: 2.50, 3.50, 4.25 bpw (3.25 already measured), Qwen2.5-0.5B
+$P -u -m lwc.experiments.valid_eval --model Qwen/Qwen2.5-0.5B --bits 2 --group 64 \
+   --arms gptq,module --out $R/rd_q05_b2g64.jsonl  > $R/rd_q05_b2g64.log 2>&1
+$P -u -m lwc.experiments.valid_eval --model Qwen/Qwen2.5-0.5B --bits 3 --group 64 \
+   --arms gptq,module --out $R/rd_q05_b3g64.jsonl  > $R/rd_q05_b3g64.log 2>&1
+$P -u -m lwc.experiments.valid_eval --model Qwen/Qwen2.5-0.5B --bits 4 --group 128 \
+   --arms gptq,module --out $R/rd_q05_b4g128.jsonl > $R/rd_q05_b4g128.log 2>&1
+touch $R/RD_DONE
+# (2) the scaling point
+$P -u -m lwc.experiments.valid_eval --model unsloth/Llama-3.2-3B --calib-seed 0 \
+   --arms gptq,module --out $R/p6_llama3b_s0.jsonl > $R/p6_llama3b_s0.log 2>&1
+touch $R/P6_DONE

evidence/box_scripts/lwc_p3.sh

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+#!/bin/bash
+cd /root/lwc/repo_new || exit 1
+export PYTHONPATH=src OMP_NUM_THREADS=16 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
+P=/venv/main/bin/python
+R=/root/lwc/results
+$P -u -m lwc.experiments.valid_eval --model unsloth/Llama-3.2-1B --calib-seed 0 \
+   --fresh-g-seq 16 --arms gptq,layer,module --out $R/p3_llama1b.jsonl > $R/p3_llama1b.log 2>&1
+touch $R/P3_DONE

evidence/box_scripts/lwc_p3b.sh

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+#!/bin/bash
+cd /root/lwc/repo_new || exit 1
+export PYTHONPATH=src OMP_NUM_THREADS=16 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
+P=/venv/main/bin/python
+R=/root/lwc/results
+for s in 1 2; do
+  $P -u -m lwc.experiments.valid_eval --model unsloth/Llama-3.2-1B --calib-seed $s \
+     --fresh-g-seq 16 --arms gptq,module --out $R/p3_llama1b_s$s.jsonl > $R/p3_llama1b_s$s.log 2>&1 || break
+done
+touch $R/P3B_DONE

evidence/box_scripts/lwc_p4.sh

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+#!/bin/bash
+# P4: Llama-3.2-3B -- matches the failing Qwen2.5-1.5B on BOTH untested candidate features
+# (28 layers, head_dim 128) while differing in family and size. Frozen protocol, no tuning.
+cd /root/lwc/repo_new || exit 1
+export PYTHONPATH=src OMP_NUM_THREADS=16 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
+P=/venv/main/bin/python
+R=/root/lwc/results
+for s in 0 1; do
+  $P -u -m lwc.experiments.valid_eval --model unsloth/Llama-3.2-3B --calib-seed $s \
+     --fresh-g-seq 16 --arms gptq,module --out $R/p4_llama3b_s$s.jsonl > $R/p4_llama3b_s$s.log 2>&1 || break
+done
+touch $R/P4_DONE

evidence/box_scripts/lwc_p5.sh

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+#!/bin/bash
+cd /root/lwc/repo_new || exit 1
+export PYTHONPATH=src OMP_NUM_THREADS=16 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
+/venv/main/bin/python -u -m lwc.experiments.valid_eval --model Qwen/Qwen2.5-1.5B \
+  --calib-seed 1 --arms gptq,module --out /root/lwc/results/valid_qwen15_s1b.jsonl \
+  > /root/lwc/results/valid_qwen15_s1b.log 2>&1
+touch /root/lwc/results/P5_DONE

evidence/box_scripts/lwc_sweep.sh

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+#!/bin/bash
+cd /root/lwc/repo_new || exit 1
+export PYTHONPATH=src OMP_NUM_THREADS=16 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
+P=/venv/main/bin/python
+R=/root/lwc/results
+echo "=== Qwen2.5-1.5B layer 13 ==="
+$P -u noise_probe.py --model Qwen/Qwen2.5-1.5B --layer 13 --out $R/probe_15b.jsonl 2>&1 | grep -avE 'Loading|Warning|it/s|longer than'
+echo "=== Qwen2.5-0.5B layer 11 (control: the size where the method works) ==="
+$P -u noise_probe.py --model Qwen/Qwen2.5-0.5B --layer 11 --out $R/probe_05b.jsonl 2>&1 | grep -avE 'Loading|Warning|it/s|longer than'
+touch $R/SWEEP_DONE

evidence/diagnostics/attn_decomp.jsonl

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+{"layer": 5, "arm": "layer", "bits": 3, "group": 128, "secs": 4.954832553863525, "cal_logit_mse": 0.07936648279428482, "cal_softmax_kl": 0.016481926664710045, "cal_attnout_mse": 0.0006425523315556347, "cal_top1_flips": 0.0548444464802742, "val_logit_mse": 0.09921277314424515, "val_softmax_kl": 0.020411429926753044, "val_attnout_mse": 0.0008493068744428456, "val_top1_flips": 0.0611310675740242, "dmg_q_proj": 6.6955342292785645, "dmg_k_proj": 1.2423218488693237, "rho_zmax_kl": 0.0457700751721859, "rho_zmax_dY": 0.1648099571466446, "rho_margin_kl": -0.36383548378944397, "rho_margin_dY": -0.5051407814025879, "rho_entropy_kl": 0.4951394200325012, "rho_entropy_dY": 0.19192469120025635, "rho_pmax_kl": -0.5112256407737732, "rho_pmax_dY": -0.38153886795043945, "rho_jtrace_kl": 0.5207735896110535, "rho_jtrace_dY": 0.34042859077453613, "rho_v_disp_kl": 0.586668848991394, "rho_v_disp_dY": 0.5092847347259521, "rho_vdisp_dY_at_fixed_kl": 0.13909018374979495, "n_rows": 20000}
+{"layer": 5, "arm": "logits", "bits": 3, "group": 128, "secs": 74.82016062736511, "cal_logit_mse": 0.0372544564306736, "cal_softmax_kl": 0.008180066011846066, "cal_attnout_mse": 0.0003269195731263608, "cal_top1_flips": 0.04071044921875, "val_logit_mse": 0.05015130713582039, "val_softmax_kl": 0.010623576119542122, "val_attnout_mse": 0.0004404713399708271, "val_top1_flips": 0.0472324900329113, "dmg_q_proj": 7.371162414550781, "dmg_k_proj": 1.380376935005188}
+{"layer": 5, "arm": "softmax", "bits": 3, "group": 128, "secs": 64.2379059791565, "cal_logit_mse": 0.0404399074614048, "cal_softmax_kl": 0.007680214941501617, "cal_attnout_mse": 0.00029621770954690874, "cal_top1_flips": 0.0385916568338871, "val_logit_mse": 0.054278455674648285, "val_softmax_kl": 0.010163349099457264, "val_attnout_mse": 0.0004112136084586382, "val_top1_flips": 0.0458984375, "dmg_q_proj": 7.227158546447754, "dmg_k_proj": 1.3936494588851929}
+{"layer": 5, "arm": "attn_out", "bits": 3, "group": 128, "secs": 73.49855923652649, "cal_logit_mse": 0.04366161674261093, "cal_softmax_kl": 0.008489513769745827, "cal_attnout_mse": 0.0003284865233581513, "cal_top1_flips": 0.0400739386677742, "val_logit_mse": 0.05820653960108757, "val_softmax_kl": 0.010972641408443451, "val_attnout_mse": 0.00043945456854999065, "val_top1_flips": 0.0465872623026371, "dmg_q_proj": 7.401889324188232, "dmg_k_proj": 1.4127721786499023}
+{"layer": 11, "arm": "layer", "bits": 3, "group": 128, "secs": 7.0500569343566895, "cal_logit_mse": 0.13208012282848358, "cal_softmax_kl": 0.015558155253529549, "cal_attnout_mse": 0.0012256234185770154, "cal_top1_flips": 0.0506853386759758, "val_logit_mse": 0.16670933365821838, "val_softmax_kl": 0.017973612993955612, "val_attnout_mse": 0.0013338716235011816, "val_top1_flips": 0.05438232421875, "dmg_q_proj": 7.7021589279174805, "dmg_k_proj": 1.3697181940078735, "rho_zmax_kl": -0.6388855576515198, "rho_zmax_dY": -0.6148338317871094, "rho_margin_kl": -0.8533724546432495, "rho_margin_dY": -0.8314241170883179, "rho_entropy_kl": 0.8623368144035339, "rho_entropy_dY": 0.7708290815353394, "rho_pmax_kl": -0.8775475025177002, "rho_pmax_dY": -0.8010557293891907, "rho_jtrace_kl": 0.8749730587005615, "rho_jtrace_dY": 0.7909843921661377, "rho_v_disp_kl": 0.8758155107498169, "rho_v_disp_dY": 0.8050832152366638, "rho_vdisp_dY_at_fixed_kl": 0.1321571335196495, "n_rows": 20000}
+{"layer": 11, "arm": "logits", "bits": 3, "group": 128, "secs": 53.54718279838562, "cal_logit_mse": 0.07650519907474518, "cal_softmax_kl": 0.00952737033367157, "cal_attnout_mse": 0.0007060313946567476, "cal_top1_flips": 0.0417916439473629, "val_logit_mse": 0.10239462554454803, "val_softmax_kl": 0.011604377068579197, "val_attnout_mse": 0.0008334100130014122, "val_top1_flips": 0.0461251400411129, "dmg_q_proj": 8.297468185424805, "dmg_k_proj": 1.5274287462234497}
+{"layer": 11, "arm": "softmax", "bits": 3, "group": 128, "secs": 46.26942729949951, "cal_logit_mse": 0.09054058790206909, "cal_softmax_kl": 0.008696121163666248, "cal_attnout_mse": 0.0006874556420370936, "cal_top1_flips": 0.0402047298848629, "val_logit_mse": 0.1188141331076622, "val_softmax_kl": 0.01072769332677126, "val_attnout_mse": 0.0008272708510048687, "val_top1_flips": 0.0448695607483387, "dmg_q_proj": 8.196929931640625, "dmg_k_proj": 1.5175254344940186}
+{"layer": 11, "arm": "attn_out", "bits": 3, "group": 128, "secs": 46.876134157180786, "cal_logit_mse": 0.08758528530597687, "cal_softmax_kl": 0.00856199860572815, "cal_attnout_mse": 0.0006219701608642936, "cal_top1_flips": 0.0400565005838871, "val_logit_mse": 0.11507723480463028, "val_softmax_kl": 0.010698885656893253, "val_attnout_mse": 0.0007820582832209766, "val_top1_flips": 0.0452532097697258, "dmg_q_proj": 8.473241806030273, "dmg_k_proj": 1.5463701486587524}
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evidence/diagnostics/calib_size.jsonl

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evidence/diagnostics/d2_qwen05_bd.jsonl

@@ -0,0 +1,5 @@
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evidence/diagnostics/d2_qwen05_bd.log

@@ -0,0 +1,11 @@
+Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.
+
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (299078 > 131072). Running this sequence through the model will result in indexing errors
+eval sets: wt2 146 windows, c4 512 windows, kl 64 windows
+fp16 wt2 mean NLL 2.57032  (ppl 13.0700)  20s
+fp16 c4  mean NLL 3.04347  (ppl 20.9778)  63s
+  layer  0/23  peak 2040 MiB  opt 135s
+  layer  8/23  peak 2431 MiB  opt 1422s
+  layer 16/23  peak 2818 MiB  opt 2728s
+  layer 23/23  peak 3157 MiB  opt 3836s
+module_bd bpw 3.2500 | NLL wt2 2.89882 c4 3.39350 | KL 0.34641 | 4190s

evidence/diagnostics/d2_qwen15_bd.jsonl

@@ -0,0 +1,5 @@
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evidence/diagnostics/d2_qwen15_bd.log

@@ -0,0 +1,12 @@
+Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.
+
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (299078 > 131072). Running this sequence through the model will result in indexing errors
+eval sets: wt2 146 windows, c4 512 windows, kl 64 windows
+fp16 wt2 mean NLL 2.22623  (ppl 9.2649)  22s
+fp16 c4  mean NLL 2.74330  (ppl 15.5382)  71s
+  layer  0/27  peak 6511 MiB  opt 137s
+  layer  8/27  peak 7551 MiB  opt 2722s
+  layer 16/27  peak 8585 MiB  opt 5358s
+  layer 24/27  peak 9619 MiB  opt 7857s
+  layer 27/27  peak 10007 MiB  opt 8733s
+module_bd bpw 3.2500 | NLL wt2 2.55952 c4 3.06488 | KL 0.35413 | 9314s

evidence/diagnostics/d2_qwen15_pre.jsonl

@@ -0,0 +1,5 @@
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evidence/diagnostics/d2_qwen15_pre.log

@@ -0,0 +1,12 @@
+Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.
+
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (299078 > 131072). Running this sequence through the model will result in indexing errors
+eval sets: wt2 146 windows, c4 512 windows, kl 64 windows
+fp16 wt2 mean NLL 2.22623  (ppl 9.2649)  22s
+fp16 c4  mean NLL 2.74330  (ppl 15.5382)  70s
+  layer  0/27  peak 6511 MiB  opt 129s
+  layer  8/27  peak 7551 MiB  opt 2574s
+  layer 16/27  peak 8585 MiB  opt 5234s
+  layer 24/27  peak 9619 MiB  opt 7888s
+  layer 27/27  peak 10007 MiB  opt 8947s
+module_pre bpw 3.2500 | NLL wt2 2.55624 c4 3.06125 | KL 0.35420 | 9511s

evidence/diagnostics/gptq_scalefeed.jsonl

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+{"module": "1.mlp.down_proj", "coord": "native", "bits": 4, "group": 256, "arm": "order:reverse", "d": 0.003990638508850027}
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evidence/diagnostics/joint_oracle_k.jsonl

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evidence/diagnostics/joint_ppl.jsonl

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evidence/diagnostics/noise_probe.jsonl

@@ -0,0 +1,5 @@
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+{"module": "self_attn.k_proj", "dim": 256, "believed": 0.356057858021298, "actual": 0.41524306207708744, "n_low": 2048, "n_high": 16384}
+{"module": "self_attn.q_proj", "dim": 1536, "believed": 0.6484209325191876, "actual": 0.6667364072461297, "n_low": 2048, "n_high": 16384}
+{"module": "self_attn.v_proj", "dim": 256, "believed": 0.8082564726253219, "actual": 0.9859142290018968, "n_low": 2048, "n_high": 16384}

evidence/diagnostics/probe_05b.jsonl

@@ -0,0 +1,5 @@
+{"module": "mlp.gate_proj", "dim": 4864, "believed": 0.6711511220781919, "samp_per_dim": 0.42105263157894735, "scored": {"4096": 0.8349105419044976, "8192": 0.9180760472084851, "16384": 1.0011232605039764, "32768": 1.0013728810497589}}
+{"module": "mlp.up_proj", "dim": 4864, "believed": 0.6937906372339927, "samp_per_dim": 0.42105263157894735, "scored": {"4096": 0.7478018507300166, "8192": 0.7751277625197365, "16384": 0.8021502302396051, "32768": 0.8022569906806791}}
+{"module": "self_attn.k_proj", "dim": 128, "believed": 0.5037461848558463, "samp_per_dim": 16.0, "scored": {"4096": 0.554214605631036, "8192": 0.5752003747613657, "16384": 0.5883852062996466, "32768": 0.6038568557781655}}
+{"module": "self_attn.q_proj", "dim": 896, "believed": 0.6852719856710527, "samp_per_dim": 2.2857142857142856, "scored": {"4096": 0.696567244154537, "8192": 0.700055715811036, "16384": 0.7027678607724606, "32768": 0.7035147711984908}}
+{"module": "self_attn.v_proj", "dim": 128, "believed": 0.4565450977875202, "samp_per_dim": 16.0, "scored": {"4096": 0.925283926028205, "8192": 0.9867420216931289, "16384": 1.0534924437326636, "32768": 1.0923346339043059}}

evidence/diagnostics/probe_15b.jsonl

@@ -0,0 +1,5 @@
+{"module": "mlp.gate_proj", "dim": 8960, "believed": 0.6153810434643856, "samp_per_dim": 0.22857142857142856, "scored": {"4096": 0.8405664165722594, "8192": 0.9526340657202459, "16384": 1.0646924000492919, "32768": 1.064702934133185}}
+{"module": "mlp.up_proj", "dim": 8960, "believed": 0.6360403366949652, "samp_per_dim": 0.22857142857142856, "scored": {"4096": 0.8215899677450879, "8192": 0.9147525252809561, "16384": 1.0080371809415114, "32768": 1.0080413457226802}}
+{"module": "self_attn.k_proj", "dim": 256, "believed": 0.356057858021298, "samp_per_dim": 8.0, "scored": {"4096": 0.40621852492100036, "8192": 0.4035259661520504, "16384": 0.41524306207708744, "32768": 0.43187361736879387}}
+{"module": "self_attn.q_proj", "dim": 1536, "believed": 0.6508336235847655, "samp_per_dim": 1.3333333333333333, "scored": {"4096": 0.6618089121912499, "8192": 0.667980063764893, "16384": 0.6694334097747758, "32768": 0.6717516371940631}}
+{"module": "self_attn.v_proj", "dim": 256, "believed": 0.8082564726253219, "samp_per_dim": 8.0, "scored": {"4096": 0.9122843558063494, "8192": 0.9586694013192353, "16384": 0.9859142290018968, "32768": 0.9994320757877531}}

evidence/diagnostics/rate_alloc.jsonl

@@ -0,0 +1,26 @@
+{"module": "model.layers.1.mlp.down_proj", "granularity": "row", "budget": 2.5, "used_bpw": 2.5, "n_rungs_used": 3, "d_uniform": 0.055746483951655955, "d_alloc": 0.05476749857206734, "gain_frac": 0.017561383430703903, "eq_bpw_gain": -0.02611336478651749, "secs": 109.9245924949646, "dv_uniform": 0.17029045309541363, "dv_alloc": 0.17224441926325398}
+{"module": "model.layers.1.mlp.down_proj", "granularity": "row", "budget": 3.25, "used_bpw": 3.2488839626312256, "n_rungs_used": 2, "d_uniform": 0.01003560879186676, "d_alloc": 0.010092026795192268, "gain_frac": -0.005621781846581353, "eq_bpw_gain": 0.0010189568374232572, "secs": 109.9492404460907, "dv_uniform": 0.031788386005971864, "dv_alloc": 0.03203304338377026}
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+{"module": "model.layers.22.self_attn.q_proj", "granularity": "row", "budget": 3.25, "used_bpw": 3.2491631507873535, "n_rungs_used": 2, "d_uniform": 0.008742296480231074, "d_alloc": 0.008766576279238717, "gain_frac": -0.0027772792952682757, "eq_bpw_gain": 0.0005191631046344014, "secs": 16.79656147956848, "dv_uniform": 0.011107682404271936, "dv_alloc": 0.011157494193670119}
+{"granularity": "matrix", "budget": 2.5, "used_bpw": 2.3796296296296298, "n_matrices": 12, "d_uniform": 0.614880662546788, "d_alloc": 0.576354808639735, "gain_frac": 0.06265582291607918}
+{"granularity": "matrix", "budget": 3.25, "used_bpw": 3.25, "n_matrices": 12, "d_uniform": 0.1210418525584256, "d_alloc": 0.12104185274802148, "gain_frac": -1.5663663699427843e-09}

evidence/diagnostics/sweep.log

@@ -0,0 +1,12 @@
+=== Qwen2.5-1.5B layer 13 ===
+gate_proj    out  8960 (0.23 samp/dim) | believed 0.615 | scored: 4k:0.841  8k:0.953  16k:1.065  32k:1.065
+up_proj      out  8960 (0.23 samp/dim) | believed 0.636 | scored: 4k:0.822  8k:0.915  16k:1.008  32k:1.008
+k_proj       out   256 (8.00 samp/dim) | believed 0.356 | scored: 4k:0.406  8k:0.404  16k:0.415  32k:0.432
+q_proj       out  1536 (1.33 samp/dim) | believed 0.651 | scored: 4k:0.662  8k:0.668  16k:0.669  32k:0.672
+v_proj       out   256 (8.00 samp/dim) | believed 0.808 | scored: 4k:0.912  8k:0.959  16k:0.986  32k:0.999
+=== Qwen2.5-0.5B layer 11 (control: the size where the method works) ===
+gate_proj    out  4864 (0.42 samp/dim) | believed 0.671 | scored: 4k:0.835  8k:0.918  16k:1.001  32k:1.001
+up_proj      out  4864 (0.42 samp/dim) | believed 0.694 | scored: 4k:0.748  8k:0.775  16k:0.802  32k:0.802
+k_proj       out   128 (16.00 samp/dim) | believed 0.504 | scored: 4k:0.554  8k:0.575  16k:0.588  32k:0.604
+q_proj       out   896 (2.29 samp/dim) | believed 0.685 | scored: 4k:0.697  8k:0.700  16k:0.703  32k:0.704
+v_proj       out   128 (16.00 samp/dim) | believed 0.457 | scored: 4k:0.925  8k:0.987  16k:1.053  32k:1.092

evidence/diagnostics/transform_plateau.jsonl

@@ -0,0 +1,14 @@
+{"module": "model.layers.11.self_attn.q_proj", "mode": "tangent", "eps": 0.01, "dirs": 50, "base": 0.006167055861708993, "noise_spread": 0.0, "frac_better": 0.18, "best": -0.003472337471620679, "p10": -0.0007995873771109441, "median": 0.001886215682976644, "worst": 0.005557206859296171, "mean": 0.0017593396144203765, "secs": 205.18055510520935}
+{"module": "model.layers.11.self_attn.q_proj", "mode": "tangent", "eps": 0.03, "dirs": 50, "base": 0.006167055861708993, "noise_spread": 0.0, "frac_better": 0.3, "best": -0.0028399523678639405, "p10": -0.0014447146615508277, "median": 0.0011078859926638707, "worst": 0.006559053045884777, "mean": 0.0012293879688205877, "secs": 272.7775881290436}
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evidence/validation/d3a_qwen05_halves_s0.log

@@ -0,0 +1,18 @@
+Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.
+
+<repo>/.venv\Lib\site-packages\torch\nn\modules\module.py:1329: UserWarning: expandable_segments not supported on this platform (Triggered internally at C:\actions-runner\_work\pytorch\pytorch\pytorch\c10/cuda/CUDAAllocatorConfig.h:28.)
+  return t.to(
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (299078 > 131072). Running this sequence through the model will result in indexing errors
+eval sets: wt2 146 windows, c4 512 windows, kl 64 windows
+fp16 wt2 mean NLL 2.57033  (ppl 13.0701)  170s
+fp16 c4  mean NLL 3.04346  (ppl 20.9777)  567s
+  layer  0/23  peak 1837 MiB  opt 45s
+  layer  8/23  peak 2238 MiB  opt 391s
+  layer 16/23  peak 2632 MiB  opt 717s
+  layer 23/23  peak 2979 MiB  opt 984s
+module_attn bpw 3.2500 | NLL wt2 2.91925 c4 3.40435 | KL 0.36478 | 1143s
+  layer  0/23  peak 2723 MiB  opt 56s
+  layer  8/23  peak 2888 MiB  opt 701s
+  layer 16/23  peak 3051 MiB  opt 1364s
+  layer 23/23  peak 3193 MiB  opt 1971s
+module_mlp bpw 3.2500 | NLL wt2 2.91291 c4 3.39862 | KL 0.35888 | 2172s

evidence/validation/d3b_qwen05_model_p2_t2k_s0.jsonl

@@ -0,0 +1,5 @@
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evidence/validation/d3b_qwen05_model_p2_t2k_s0.log

@@ -0,0 +1,13 @@
+Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.
+
+<repo>/.venv\Lib\site-packages\torch\nn\modules\module.py:1329: UserWarning: expandable_segments not supported on this platform (Triggered internally at C:\actions-runner\_work\pytorch\pytorch\pytorch\c10/cuda/CUDAAllocatorConfig.h:28.)
+  return t.to(
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (299078 > 131072). Running this sequence through the model will result in indexing errors
+eval sets: wt2 146 windows, c4 512 windows, kl 64 windows
+fp16 wt2 mean NLL 2.57033  (ppl 13.0701)  178s
+fp16 c4  mean NLL 3.04346  (ppl 20.9777)  594s
+  layer  0/23  peak 3983 MiB  opt 327s
+  layer  8/23  peak 4052 MiB  opt 3221s
+  layer 16/23  peak 4052 MiB  opt 5553s
+  layer 23/23  peak 4052 MiB  opt 7089s
+model  bpw 3.2500 | NLL wt2 2.92022 c4 3.39892 | KL 0.35901 | 7602s

evidence/validation/d3b_qwen05_model_p2_t8k_s0.jsonl

@@ -0,0 +1,5 @@
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+{"model": "Qwen/Qwen2.5-0.5B", "calib_seed": 0, "seqlen": 2048, "calib_source": "wikitext2", "n_probe": 2, "g_tokens": 8192, "arm": "model", "bpw": 3.2500150240384613, "flips": {"q_proj": 0.027774369635549533, "depth0": 0.02659336411472642, "k_proj": 0.03210594540550595, "v_proj": 0.02516137985956101, "o_proj": 0.02046208803345557, "gate_proj": 0.027554801233430255, "up_proj": 0.025750344259697095, "down_proj": 0.02978676243832237, "depth1": 0.02963973384200435, "depth2": 0.028742338187528617, "depth3": 0.024329641712454213}, "obj_ratio": 0.8797039433647955, "obj_fresh": 0.7546398353692625, "obj_fresh_before": 0.6640191683018202, "obj_fresh_after": 0.4506922442778887, "quant_s": 5810.363184928894, "opt_s": 5329.310094594955, "scope_s": 215.1662518978119, "peak_vram_mib": 4051.68994140625, "nll_wt2": 2.901985325225412, "nll_c4": 3.3934311794582754, "kl_fp16": 0.34935207810485736}

evidence/validation/d3b_qwen05_model_p2_t8k_s0.log

@@ -0,0 +1,13 @@
+Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.
+
+<repo>/.venv\Lib\site-packages\torch\nn\modules\module.py:1329: UserWarning: expandable_segments not supported on this platform (Triggered internally at C:\actions-runner\_work\pytorch\pytorch\pytorch\c10/cuda/CUDAAllocatorConfig.h:28.)
+  return t.to(
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (299078 > 131072). Running this sequence through the model will result in indexing errors
+eval sets: wt2 146 windows, c4 512 windows, kl 64 windows
+fp16 wt2 mean NLL 2.57033  (ppl 13.0701)  170s
+fp16 c4  mean NLL 3.04346  (ppl 20.9777)  568s
+  layer  0/23  peak 3983 MiB  opt 190s
+  layer  8/23  peak 4052 MiB  opt 2289s
+  layer 16/23  peak 4052 MiB  opt 4195s
+  layer 23/23  peak 4052 MiB  opt 5329s
+model  bpw 3.2500 | NLL wt2 2.90199 c4 3.39343 | KL 0.34935 | 5810s

evidence/validation/d3b_qwen05_model_p8_t2k_s0.jsonl

@@ -0,0 +1,5 @@
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+{"model": "Qwen/Qwen2.5-0.5B", "calib_seed": 0, "seqlen": 2048, "calib_source": "wikitext2", "n_probe": 8, "g_tokens": 2048, "arm": "model", "bpw": 3.2500150240384613, "flips": {"q_proj": 0.028382022364609908, "depth0": 0.024272943853021978, "k_proj": 0.032552083333333336, "v_proj": 0.026484898158482144, "o_proj": 0.02249892877072704, "gate_proj": 0.025720830549273575, "up_proj": 0.0248410695776306, "down_proj": 0.03215826125372024, "depth1": 0.02891598656063988, "depth2": 0.030676683139451693, "depth3": 0.025628840966975732}, "obj_ratio": 0.8542424156304261, "obj_fresh": 0.7965895478199045, "obj_fresh_before": 0.7503775288532779, "obj_fresh_after": 0.528526462152513, "quant_s": 12642.852195501328, "opt_s": 10234.404404640198, "scope_s": 1326.7690033912659, "peak_vram_mib": 4051.68994140625, "nll_wt2": 2.9252870915687246, "nll_c4": 3.401589708868414, "kl_fp16": 0.36468208074802533}

evidence/validation/d3b_qwen05_model_p8_t2k_s0.log

@@ -0,0 +1,13 @@
+Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.
+
+<repo>/.venv\Lib\site-packages\torch\nn\modules\module.py:1329: UserWarning: expandable_segments not supported on this platform (Triggered internally at C:\actions-runner\_work\pytorch\pytorch\pytorch\c10/cuda/CUDAAllocatorConfig.h:28.)
+  return t.to(
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (299078 > 131072). Running this sequence through the model will result in indexing errors
+eval sets: wt2 146 windows, c4 512 windows, kl 64 windows
+fp16 wt2 mean NLL 2.57033  (ppl 13.0701)  172s
+fp16 c4  mean NLL 3.04346  (ppl 20.9777)  576s
+  layer  0/23  peak 3983 MiB  opt 481s
+  layer  8/23  peak 4052 MiB  opt 4868s
+  layer 16/23  peak 4052 MiB  opt 8357s
+  layer 23/23  peak 4052 MiB  opt 10234s
+model  bpw 3.2500 | NLL wt2 2.92529 c4 3.40159 | KL 0.36468 | 12642s

evidence/validation/d3bx2_qwen05_module_t8k_s0.jsonl

@@ -0,0 +1,5 @@
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evidence/validation/d3bx2_qwen05_module_t8k_s0.log

@@ -0,0 +1,11 @@
+Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.
+
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (299078 > 131072). Running this sequence through the model will result in indexing errors
+eval sets: wt2 146 windows, c4 512 windows, kl 64 windows
+fp16 wt2 mean NLL 2.57033  (ppl 13.0701)  170s
+fp16 c4  mean NLL 3.04346  (ppl 20.9777)  568s
+  layer  0/23  peak 2051 MiB  opt 99s
+  layer  8/23  peak 2449 MiB  opt 1065s
+  layer 16/23  peak 2843 MiB  opt 2070s
+  layer 23/23  peak 3189 MiB  opt 2870s
+module bpw 3.2500 | NLL wt2 2.89554 c4 3.38287 | KL 0.34193 | 3109s

evidence/validation/d3bx_qwen05_attn_t8k_s0.jsonl

@@ -0,0 +1,5 @@
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evidence/validation/d3bx_qwen05_attn_t8k_s0.log

@@ -0,0 +1,11 @@
+Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.
+
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (299078 > 131072). Running this sequence through the model will result in indexing errors
+eval sets: wt2 146 windows, c4 512 windows, kl 64 windows
+fp16 wt2 mean NLL 2.57033  (ppl 13.0701)  170s
+fp16 c4  mean NLL 3.04346  (ppl 20.9777)  570s
+  layer  0/23  peak 1837 MiB  opt 89s
+  layer  8/23  peak 2238 MiB  opt 701s
+  layer 16/23  peak 2632 MiB  opt 1266s
+  layer 23/23  peak 2979 MiB  opt 1707s
+module_attn bpw 3.2500 | NLL wt2 2.89803 c4 3.38153 | KL 0.34078 | 1966s

evidence/validation/d3c_qwen05_c4calib_s0.jsonl

@@ -0,0 +1,8 @@
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+{"model": "Qwen/Qwen2.5-0.5B", "calib_seed": 0, "seqlen": 2048, "calib_source": "c4", "n_probe": 2, "g_tokens": 2048, "arm": "module", "bpw": 3.2500150240384613, "flips": {"q_proj": 0.02646403409996811, "depth0": 0.02829920730311355, "k_proj": 0.03269377208891369, "v_proj": 0.023282732282366072, "o_proj": 0.01084152533083546, "gate_proj": 0.03726705871429061, "up_proj": 0.031105127549709233, "down_proj": 0.015833737557394464, "depth1": 0.03078638992030105, "depth2": 0.027047818920987867, "depth3": 0.022080138489440248}, "obj_ratio": 0.8917268807771466, "obj_fresh": 0.7728550275137205, "obj_fresh_before": 99.56737052865174, "obj_fresh_after": 74.25418122423616, "quant_s": 2878.647147655487, "opt_s": 2681.320229768753, "scope_s": 32.44763970375061, "peak_vram_mib": 3191.111328125, "nll_wt2": 2.984551530994781, "nll_c4": 3.3617620549630374, "kl_fp16": 0.3705406843801029}

evidence/validation/d3c_qwen05_c4calib_s0.log

@@ -0,0 +1,18 @@
+Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.
+
+<repo>/.venv\Lib\site-packages\torch\nn\modules\module.py:1329: UserWarning: expandable_segments not supported on this platform (Triggered internally at C:\actions-runner\_work\pytorch\pytorch\pytorch\c10/cuda/CUDAAllocatorConfig.h:28.)
+  return t.to(
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (299078 > 131072). Running this sequence through the model will result in indexing errors
+eval sets: wt2 146 windows, c4 512 windows, kl 64 windows
+fp16 wt2 mean NLL 2.57033  (ppl 13.0701)  169s
+fp16 c4  mean NLL 3.04346  (ppl 20.9777)  565s
+  layer  0/23  peak 1797 MiB  opt 0s
+  layer  8/23  peak 1964 MiB  opt 0s
+  layer 16/23  peak 2124 MiB  opt 0s
+  layer 23/23  peak 2264 MiB  opt 0s
+gptq   bpw 3.2500 | NLL wt2 3.02064 c4 3.39272 | KL 0.40091 | 134s
+  layer  0/23  peak 2051 MiB  opt 91s
+  layer  8/23  peak 2449 MiB  opt 1025s
+  layer 16/23  peak 2846 MiB  opt 1913s
+  layer 23/23  peak 3191 MiB  opt 2681s
+module bpw 3.2500 | NLL wt2 2.98455 c4 3.36176 | KL 0.37054 | 2878s

evidence/validation/d4_qwen05_vq20_prefix.jsonl

@@ -0,0 +1,4 @@
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evidence/validation/d4_qwen05_vq20_prefix_plain.log

@@ -0,0 +1,5 @@
+
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (299078 > 131072). Running this sequence through the model will result in indexing errors
+prefix tokens: [271]
+vq20_plain wt2 prefixed mean NLL 3.20277
+vq20_plain c4 prefixed mean NLL 3.94439

evidence/validation/d4_qwen05_vq20_prefix_refine.log

@@ -0,0 +1,5 @@
+
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (299078 > 131072). Running this sequence through the model will result in indexing errors
+prefix tokens: [271]
+vq20_refine wt2 prefixed mean NLL 3.17293
+vq20_refine c4 prefixed mean NLL 3.91441

evidence/validation/monitor_rd_and_llama3b.log

@@ -0,0 +1,7 @@
+gptq   bpw 2.5000 | NLL wt2 9.04084 c4 9.52212 | KL 6.44220 | 220s
+module bpw 2.5000 | NLL wt2 9.13459 c4 10.44663 | KL 6.95923 | 4277s
+gptq   bpw 3.5000 | NLL wt2 2.83137 c4 3.31496 | KL 0.27972 | 230s
+module bpw 3.5000 | NLL wt2 2.82595 c4 3.31256 | KL 0.26985 | 4085s
+gptq   bpw 4.2500 | NLL wt2 2.63769 c4 3.10592 | KL 0.06652 | 226s
+module bpw 4.2500 | NLL wt2 2.63171 c4 3.10236 | KL 0.06312 | 3933s
+gptq   bpw 3.2500 | NLL wt2 2.36377 c4 3.13628 | KL 0.42679 | 517s

evidence/validation/p3_llama1b.jsonl

@@ -0,0 +1,11 @@
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+{"model": "unsloth/Llama-3.2-1B", "calib_seed": 0, "seqlen": 2048, "arm": "module", "bpw": 3.2500036831559806, "flips": {"q_proj": 0.02066972851753235, "depth0": 0.03147540010254959, "k_proj": 0.028054118156433105, "v_proj": 0.0249326229095459, "o_proj": 0.006800219416618347, "gate_proj": 0.03194717317819595, "up_proj": 0.033806800842285156, "down_proj": 0.010772354900836945, "depth1": 0.022927658311251937, "depth2": 0.022617007124012913, "depth3": 0.018654954844507677}, "obj_ratio": 0.8575393948519975, "obj_fresh": 0.7772178773354647, "obj_fresh_before": 15.406506945961155, "obj_fresh_after": 14.147555806819582, "quant_s": 10479.94899892807, "opt_s": 10104.40731883049, "scope_s": 13.990835428237915, "peak_vram_mib": 8527.8681640625, "nll_wt2": 2.743179755007967, "nll_c4": 3.475291386945173, "kl_fp16": 0.6140267107402906}

evidence/validation/p3_llama1b.log

@@ -0,0 +1,18 @@
+Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.
+
+[transformers] Token indices sequence length is longer than the specified maximum sequence length for this model (289077 > 131072). Running this sequence through the model will result in indexing errors
+eval sets: wt2 141 windows, c4 512 windows, kl 64 windows
+fp16 wt2 mean NLL 2.27737  (ppl 9.7510)  14s
+fp16 c4  mean NLL 2.78521  (ppl 16.2032)  44s
+  layer  0/15  peak 4798 MiB  opt 0s
+  layer  8/15  peak 5446 MiB  opt 0s
+  layer 15/15  peak 6006 MiB  opt 0s
+gptq   bpw 3.2500 | NLL wt2 2.76574 c4 3.49985 | KL 0.62934 | 307s
+  layer  0/15  peak 4814 MiB  opt 72s
+  layer  8/15  peak 5462 MiB  opt 656s
+  layer 15/15  peak 6022 MiB  opt 1169s
+layer  bpw 3.2500 | NLL wt2 2.78013 c4 3.51777 | KL 0.65332 | 1500s
+  layer  0/15  peak 5580 MiB  opt 501s
+  layer  8/15  peak 7156 MiB  opt 5679s
+  layer 15/15  peak 8528 MiB  opt 10104s
+module bpw 3.2500 | NLL wt2 2.74318 c4 3.47529 | KL 0.61403 | 10479s

evidence/validation/p3_llama1b_s1.jsonl

@@ -0,0 +1,8 @@
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