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v3 (cc12) ONNX artifacts + decoder gradient graph
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v3 (cc12) ONNX artifacts + decoder gradient graph
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v3 (cc12) ONNX artifacts + decoder gradient graph
6d40bd3
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arodland commited on

v3 (cc12) ONNX artifacts + decoder gradient graph
1b87647
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arodland commited on

v3 (cc12) ONNX artifacts + decoder gradient graph
28443d9
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arodland commited on

v3 (cc12) ONNX artifacts + decoder gradient graph
2f517ae
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arodland commited on

v3 (cc12) ONNX artifacts + decoder gradient graph
62d28c2
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arodland commited on

v3 (cc12) ONNX artifacts + decoder gradient graph
3d8e562
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v3 (cc12) ONNX artifacts + decoder gradient graph
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v2 checkpoint: s2 + nonphoto-frac 0.1 fine-tune (epoch 317)
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ONNX artifacts for v2.pt
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ONNX artifacts for v2.pt
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ONNX artifacts for v2.pt
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ONNX artifacts for v2.pt
bce99d9
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ONNX artifacts for v2.pt
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ONNX artifacts for v2.pt
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ONNX artifacts for v2.pt
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export: measured per-layer int8 tuning against off-distribution probes
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model card: tuned int8 figures
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int8: keep each part's most quantisation-sensitive layer at fp32, tuned against off-distribution probes
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re-export: int8 encoder keeps its most quantisation-sensitive layer at fp32 (5.8 -> 14.0 dB under channel noise)
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model card: document the ONNX artifacts
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publish-time ONNX export script
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ONNX artifacts for v1.pt
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ONNX artifacts for v1.pt
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ONNX artifacts for v1.pt
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ONNX artifacts for v1.pt
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ONNX artifacts for v1.pt
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ONNX artifacts for v1.pt
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ONNX artifacts for v1.pt
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link the project repository
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add model card
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default to the published checkpoint when --model is omitted
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keep only model/training code (match sstvae-code minus train_job.py)
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add project source, CLI tools and tests (no train_job.py)
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Upload v1 checkpoint
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initial commit
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