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Commit History
21 days ago
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Visualize: ask a dataset a question, get an exact chart with the rows behind every mark (small datasets first: instant glance charts, batched model labels, drill-down, scoped follow-ups)
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23 days ago
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0.2.2: route through the authenticated optillm proxy (fast tier via DI_MIN_MAX_TOKENS), prompt fixes (plain prose, no invented specifics, no callbacks/placeholders), two-order accuracy-first preference judge, accurate dataset-card provenance
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0.2.1: give reasoning models (gpt-oss) token headroom + low reasoning effort, so grading, preference ranking and ping aren't cut off; wheel rebuilt
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README: add 'How it compares' (Invent a Dataset, Curation Studio, DataInventor)
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Default engine: openai/gpt-oss-20b via DeepInfra (more concrete answers, ~2x faster than Llama-3.1-8B in a 5-row test)
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Default engine: meta-llama/Llama-3.1-8B-Instruct via DeepInfra on HF Inference Providers (was Qwen3-4B on nscale)
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25 days ago
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Link the Sutra article
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Host the runner wheel; install from it
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Curate a corpus: clean, calibrate, create, compose on a sample, plus a recipe and runner for your own machines
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default to Qwen3-4B-Instruct-2507 on nscale; thinking-off flag now opt-in
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Add sign-in with Hugging Face and publish-to-my-account with a provenance card
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Fix the endpoint on the host: remove key, URL and model fields; add a Review step; document DI_* settings
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Cap hosted runs at 200 rows; offer 25, 50, 100, 200
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DataInventor: open-source Invent a Dataset recreation
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Upload README.md with huggingface_hub
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initial commit
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