{
 "name": "light-sufficiency-predictor-gguf8",
 "status": "draft, not uploaded",
 "exported": "2026-11-04",
 "light_model": {
  "base_model": "Qwen/Qwen3-0.6B (BF16)",
  "license": "Apache-2.0",
  "gguf_source": "unsloth/Qwen3-0.6B-GGUF/Qwen3-0.6B-BF16.gguf",
  "backend": "llama",
  "gguf_8_blocks": "model.gguf, the source GGUF cut to the first 8 blocks (token_embd, output_norm, output and blk.0 to blk.7)"
 },
 "language": "English only",
 "layers": 8,
 "llama_cpp_output": "per-token embeddings (pooling NONE), includes output_norm",
 "prompt": {
  "app_commit": "97272ef",
  "language": "English prompt",
  "target_words": 100,
  "template": "<|im_start|>user\n<document>\n{text}\n</document>\n\nSummarize the document above in about 100 words (5 sentences). Use your own words and do not copy sentences from the document. Keep only the main points. Write only the summary.<|im_end|>\n<|im_start|>assistant\n<think>\n\n</think>\n\n",
  "document_placeholder": "{text}"
 },
 "tokenization": {
  "add_bos": false,
  "parse_special": true
 },
 "doc_span_rule": "Byte offsets of every token piece in the prompt (UTF-8, concatenated pieces equal the prompt bytes). The document text occupies bytes [len(prefix), len(prefix) + len(document bytes)) with prefix = '<|im_start|>user\\n<document>\\n'. A token is a document token when its byte range overlaps that range, so the token that merges the last document character with the following newline is included. The document text is used as given, not stripped.",
 "pooling": "Mean over the document tokens of the per-token embeddings (llama.cpp pooling NONE, output after output_norm of block 8), one float32 vector of 1024 values.",
 "probe": {
  "file": "probe.json",
  "formula": "z = w.x + b; p_sufficient = sigmoid(A * z + B); p_insufficient = 1 - p_sufficient",
  "platt": {
   "A": 0.9374034404754639,
   "B": 0.22994965314865112
  },
  "fold_max_abs_diff": 3.743143861534293e-08
 },
 "label": "Label v2: sufficient (1) when the light summary passes the technical checks without too_long and the Gemma 3 12B judge scores faithfulness >= 4.",
 "routing": {
  "version": 1,
  "points": [
   [
    0.0,
    0.5
   ],
   [
    0.5,
    0.8
   ],
   [
    1.0,
    0.95
   ]
  ],
  "interpolation": "linear",
  "probability": "p_sufficient",
  "rule": "light when p_sufficient >= threshold(quality_preference)",
  "chosen_on": "validation (206 texts); Platt also fitted on validation, so optimistic"
 },
 "advice": {
  "version": 1,
  "mode": "none_with_prediction",
  "rule": "with a prediction, do not suggest the heavy model; without one, the app's length advisor decides",
  "why": "on validation the probe does not separate failures among light-routed texts (see threshold_analysis.md)"
 },
 "data": {
  "train": {
   "n": 616,
   "insufficient": 104
  },
  "validation": {
   "n": 206,
   "insufficient": 30
  },
  "test": {
   "n": 151,
   "insufficient": 33
  }
 },
 "validation_results": {
  "n": 206,
  "insufficient": 30,
  "auroc": [
   0.709659090909091,
   0.5965633167023046,
   0.8156790847945943
  ],
  "ap_insufficient": [
   0.40988197040299046,
   0.25027936396129463,
   0.5809268882725719
  ],
  "hf_probe_auroc": [
   0.7147727272727273,
   0.6003268490904481,
   0.8179235442920104
  ],
  "note": "Platt is fitted on these validation texts; Brier and ECE are not reported on validation (in-sample)."
 },
 "test_results": {
  "n": 151,
  "insufficient": 33,
  "models": {
   "option 1 (GGUF 8 blocks)": {
    "auroc": [
     0.714175654853621,
     0.6110126188571936,
     0.8137687406296852
    ],
    "ap_insufficient": [
     0.4899080000407883,
     0.3316064804585212,
     0.6475444944318816
    ],
    "brier": [
     0.1548335387019752,
     0.11751881178600608,
     0.19731360723457353
    ],
    "ece": [
     0.05743244270615229,
     0.035149464366451805,
     0.1338328302005269
    ]
   },
   "HF probe": {
    "auroc": [
     0.7362609142270159,
     0.6393254108153633,
     0.8310708898944192
    ],
    "ap_insufficient": [
     0.5168968170940059,
     0.354532133131363,
     0.680021461893627
    ],
    "brier": [
     0.14991831587870777,
     0.11258698218320425,
     0.19120589099252627
    ],
    "ece": [
     0.06840796502220707,
     0.03506714001988732,
     0.13394637805539247
    ]
   },
   "(d)": {
    "auroc": [
     0.6612737544940934,
     0.552839229640059,
     0.7657977009611183
    ],
    "ap_insufficient": [
     0.4070139012278786,
     0.2702898589196186,
     0.5720459590368682
    ],
    "brier": [
     0.16557182463689082,
     0.12485330876672007,
     0.21032840020535495
    ],
    "ece": [
     0.059371011029426074,
     0.03998848389548617,
     0.14327356208017625
    ]
   }
  },
  "diffs": {
   "option 1 (GGUF 8 blocks) - (d)": [
    0.052901900359527576,
    -0.04098152794175529,
    0.1478525632814101
   ],
   "option 1 (GGUF 8 blocks) - HF probe": [
    -0.022085259373394894,
    -0.0400642421602785,
    -0.004463789682539562
   ]
  },
  "reproduction": {
   "HF probe": {
    "max_abs_diff": 0.0,
    "ok": true
   },
   "(d)": {
    "max_abs_diff": 0.0,
    "ok": true
   }
  },
  "note": "Second use of the English test set, confirmation only."
 },
 "cost": {
  "device": "llama.cpp, Metal (Apple GPU), median of 3 after a warmup",
  "per_text": [
   {
    "input_tokens": 275,
    "gguf8_embed_s": 0.072,
    "app_full_summary_s": 0.97
   },
   {
    "input_tokens": 941,
    "gguf8_embed_s": 0.231,
    "app_full_summary_s": 1.97
   },
   {
    "input_tokens": 2494,
    "gguf8_embed_s": 0.742,
    "app_full_summary_s": 2.84
   }
  ],
  "note": "gguf8_embed_s covers prompt build, tokenize and the 8-block run; the probe itself is one dot product of 1024 values."
 },
 "parity": {
  "texts": 20,
  "split": "validation",
  "domain": "government (GovReport)",
  "max_abs_diff_probability": 4.1877598239148384e-07,
  "mean_abs_diff_probability": 9.877418592485477e-08,
  "tolerance": 0.0001,
  "ok": true,
  "span_texts_checked": 822,
  "span_mismatches_vs_hf": 0,
  "span_mismatch_ids": []
 }
}