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. We fine-tuned with a Clef head using Unsloth and LoRA (r=64) for one epoch, increasing downstream accuracy from 30–37% to 78%. GitHub: github.com/unslothai/unsloth Guide and Notebooks: unsloth.ai/docs/basics/train…

Google releases EmbeddingGemma 2, a new open model that runs locally on 0.5GB RAM. The 740M parameter Apache 2.0 model combines a 270M text model with vision (170M) + audio (300M). Run & train the model via Unsloth. GGUF: huggingface.co/unsloth/embed… Guide: unsloth.ai/docs/models/embed…