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Python API: warm-up so the first real call is fast (warmup_variants, model.warmup()), quiet logs, install extras
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Python API (2026-10-04): pip install -e code/, from_pretrained() + model(...), Python-first quickstart
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Optimized build (2026-10-03): model call 2.8 ms, device 1.87 ms
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GPU_COMPARISON.md: same-host RTX 5090 benchmark of the torch reference
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tt-model.yaml: RTX 5090 comparison row + caveat
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Card: RTX 5090 comparison row + caveat
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tt-model authoring files (fused decoder, opt/rf-detr-v3-megakernel merged)
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Card: simplify the generated quickstart paragraph
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Restore card metadata (license, pipeline_tag, tags)
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tt-model push: drop 35 file(s) the bundle no longer ships
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Add files using upload-large-folder tool
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tt-model authoring files (opt/rf-detr-v2 merged)
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Card: simplify the generated quickstart paragraph
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Restore card metadata (license, pipeline_tag, tags)
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tt-model push: drop 35 file(s) the bundle no longer ships
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Add files using upload-large-folder tool
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tt-model authoring file: card trims
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Card: simplify the generated quickstart paragraph
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Restore card metadata (license, pipeline_tag, tags)
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Add files using upload-large-folder tool
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tt-model authoring file: compact card
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tt-model authoring files
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tt-model authoring files
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restore card metadata (license, pipeline_tag, tags) after tt-model push
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tt-model push: drop 43 file(s) the bundle no longer ships
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Add files using upload-large-folder tool
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tt-model authoring files
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tt-model authoring files
3eefc09
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restore card metadata (license, pipeline_tag, tags) after tt-model push
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tt-model push: drop 1 file(s) the bundle no longer ships
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Add files using upload-large-folder tool
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Add Tenstorrent Blackhole tt-nn port
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Add Tenstorrent Blackhole tt-nn port
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Add Tenstorrent Blackhole tt-nn port
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Add Tenstorrent Blackhole tt-nn port
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initial commit
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