Which open models fit your machine, how fast they run, and how many tokens it takes to pay back the hardware against an API. Honest enough to say never.
There is a subtle asymmetry in IPv6 Neighbour Discovery: a host knows how to reach its router before the router necessarily knows how to reach the host. GRAND fixes that asymmetry by making the host proactively advertise its address, and I implemented that mechanism in FreeBSD.
Run the full 2.78-trillion-parameter Kimi K3 model, DeepSeek V4.1 Flash or GLM-5.3-Flash beyond available RAM by streaming activated weights directly from NVMe. A dependency-free, embeddable C infe...
Safety alignment is only as robust as its weakest failure mode. Despite extensive work on safety post-training, it has been shown that models can be readily unaligned through post-deployment fine-tuning. However, these methods often require extensive data curation and degrade model utility. In this work, we extend the practical limits of unalignment by introducing GRP-Obliteration (GRP-Oblit), a method that uses Group Relative Policy Optimization (GRPO) to directly remove safety constraints from target models. We show that a single unlabeled prompt is sufficient to reliably unalign safety-aligned models while largely preserving their utility, and that GRP-Oblit achieves stronger unalignment on average than existing state-of-the-art techniques. Moreover, GRP-Oblit generalizes beyond language models and can also unalign diffusion-based image generation systems. We evaluate GRP-Oblit on six utility benchmarks and five safety benchmarks across fifteen 7-20B parameter models, spanning instruct and reasoning models, as well as dense and MoE architectures. The evaluated model families include GPT-OSS, distilled DeepSeek, Gemma, Llama, Ministral, and Qwen.
Lesson 2 of the free buttercup.sh agent course: the twenty-line loop that turns a chat model into an agent, working JavaScript and Python, what each turn costs in tokens, and an exercise you run in the browser.
I've been a pretty die hard Linux user for the past decade or so, it was a huge
part of my identity. Owning a shitty beaten up thinkpad and budget Android
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