Dust off your encoders: what a 25M-parameter model plus NLI can still do
MaziyarPanahi · x · 2026-09-18
Dev Maziyar Panahi recommends Hugging Face's task guides to refresh knowledge lost in the decoder-only era: encoder models remain surprisingly capable, and a 25M-parameter model using NLI (contradiction/entailment/neutral) can handle tasks like zero-shot classification. The reply jokes that 'kids these days don't know what encoders are' and teases new demos for the Jev model. A useful refresher for developers wanting cheap text classification and retrieval.
Related event: Remember Encoders: Small NLI Models Still Pack a Punch(2 posts)→
More from Models
- WeirdML v3 launches: agentic benchmark with 11 hand-made ML tasks — scaling01 · 2026-09-18
- User: Astra in Codex is unusable even on a 20x subscription — OpenAI should copy Anthropic's usage-quota approach — CtrlAltDwayne · 2026-09-18
- Grok Voice Transcribe 2.0 debuts at 97.4% accuracy, topping ElevenLabs and Gemini at $0.10/hour — XFreeze · 2026-09-18
- LightOnOCR-2-1B: 1B OCR model beats rivals 9x its size, 493K pages/day on one GPU — thisguyknowsai · 2026-09-18
- 'Astra Is OpenAI's Smartest and Dumbest Model': Users Report Wildly Inconsistent Behavior — 0xkarasy · 2026-09-18
- Another Day, Another Fake Benchmark King: 'Astra-Level' Free Models Keep Flopping — bindureddy · 2026-09-18