publish the deployment-scale artifacts the card cites
Browse files
cross_runtime_browser_rung_123k.json
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{
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"anchors": {
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"bytes": 4096,
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"n": 200,
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"source": "drawn from training-split images, disjoint from the eval gallery"
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},
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"captions": 5001,
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"encode_rate_per_s": 15.4,
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"gallery": 123287,
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"question": "does a read-out head survive a change of runtime, and does the anchor close the gap",
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"reference_runtime": "pytorch fp16 Qwen3-0.6B L28",
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"t2i": {
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"candle_q4_as_is": {
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"r@1": 0.0,
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"r@10": 0.0001999600079984003,
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"r@5": 0.0,
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"median_rank": 44578.0
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},
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"candle_q4_recalibrated": {
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"r@1": 0.03499300139972006,
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"r@10": 0.15176964607078583,
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"r@5": 0.10617876424715057,
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"median_rank": 176.0
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},
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"pytorch_fp16": {
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"r@1": 0.1092,
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"r@10": 0.3307,
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"r@5": 0.2442,
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"median_rank": 36.0
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}
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},
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"tap_layer": 28,
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"test_runtime": "Qwen3-0.6B Q4_0 (gguf, 28 layers, hidden 1024)",
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"pooling": "mean",
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"head_sha256": "09c7322a7114a174432279c8c3970260499ca1a27c5c909021f81c1f63831c4d",
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"head_note": "the bytes that ship: identical to head_v3.safetensors in the model repo and to the Space's head.safetensors",
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"index": "gallery_123k_v3.srtidx (SRTIDX02, int8, 123,287 rows) - the shipped gallery",
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"recovery_vs_reference_r@1": 0.3204,
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"supersedes": "cross_runtime_browser_rung.json, which measured an earlier 4,000-image head against a 1,000-image pool and reported 84.9% recovery",
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"pooling_note": "browser_rung's Tap::new defaults to Pooling::Last; the shipped head is mean-pooled. The first attempt at this measurement inherited that default and read 0.0136 recalibrated, which was a pooling mismatch and not a quantization result. --mean is now explicit.",
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"median_rank_note": "1-based, over the 123,287-image gallery. The anchor moves the median from 44,578 (chance is ~61,644) to 176, which is the top 0.14% of the gallery, against 36 for the fp16 reference. R@1 recovery of 32% understates the anchored arm: the correct image is usually near the top, just not at it."
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}
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