Kev Collection Jev-like family of decision models built on top of Qwen3.5/3.8 you can train and run on your own • 6 items • Updated 9 days ago • 33
kalyan-ks/Ammu-1.0-FactCheck-Need-base Text Classification • 0.1B • Updated about 14 hours ago • 38 • 1
Running on Zero Agents 1 Ammu 1.0 FactCheckNeed Classification 🐨 1 Determine whether a prompt requires factual verification (RA
Running on Zero Agents 4 Vega 0.8B Typed Decisions ⚡ 4 Typed decisions with calibrated probabilities, 73k context
view article Article Ammu-1.0-FactCheck-Need: Lightweight and Efficient Models for Fact Check Need Classification kalyan-ks • about 13 hours ago • 1
view article Article Ammu-1.0-FactCheck-Need: Lightweight and Efficient Models for Fact Check Need Classification kalyan-ks • about 13 hours ago • 1
kalyan-ks/Ammu-1.0-FactCheck-Need-small Text Classification • 68.4M • Updated about 13 hours ago • 24
kalyan-ks/Ammu-1.0-FactCheck-Need-tiny Text Classification • 32M • Updated about 13 hours ago • 30 • 1
kalyan-ks/Ammu-1.0-FactCheck-Need-base Text Classification • 0.1B • Updated about 14 hours ago • 38 • 1
view post Post 4205 You can now train your own Decision model like Jev locally!We increased Qwen3.5 0.8B’s aggregate accuracy from 20.7% to 74.3% across 3 decision benchmarks - on just 4GB VRAM.Turn any LLM like Qwen3.8, Gemma 4 into decision models with our open-source Unsloth repo.GitHub: https://github.com/unslothai/unslothGuide: https://unsloth.ai/docs/basics/train-your-own-decision-model-with-unsloth See translation 4 replies · ❤️ 17 17 🔥 8 8 👍 4 4 ➕ 2 2 🧠 2 2 + Reply
kalyan-ks/Ammu-1.0-FactCheck-Need-tiny Text Classification • 32M • Updated about 13 hours ago • 30 • 1
BioBigBird Collection Model for long context biomedical named entity recognition and relation extraction • 3 items • Updated Aug 22 • 1