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Get Started Free →Trending Hugging Face models, datasets, and spaces — filtered by license sanity, dedup vs same-week quantizations, with a "why notable" line per pick (architecture shift, size step, license change, notable author). Surfaces what's actually shifting rather than just popular. Triggers: "trending on HF", "what models are hot", "huggingface trending", "new spaces today", "best new datasets".
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -11% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -55% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 4% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 5% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -34% | 0% |
Daily filtered scan over HF's three trending surfaces — models, datasets, spaces — cluster-ranked rather than raw-download ranked.
bashcurl -s "https://huggingface.co/api/models?sort=trending&direction=-1&limit=30" curl -s "https://huggingface.co/api/datasets?sort=trending&direction=-1&limit=30" curl -s "https://huggingface.co/api/spaces?sort=trending&direction=-1&limit=30"
Per surfaced entry, a one-sentence tag: new architecture / size step / context-window jump / notable author affiliation / license change. If no concrete reason exists, the entry says "no clear why — popular but unremarkable" rather than inventing one.
Three sections — Models, Datasets, Spaces — each with the surviving picks, "why notable", license, and download/view count. Tail section for quantizations.
Other measured skills in the registry, with their headline benchmark lift.