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As of Sep 18, 11:37 PM EDT · revalidates daily
The story
jingyaogong/minimind
🧠 Train a 64M-parameter LLM from scratch in just 2h!
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15 · jingyaogong
82
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53 · 0xNatoshi
63
Per-turn model & reasoning routing for Codex, driven by Jev (TypeSafe System One): picks the model, thinking depth and speed mode for every turn.
harshitkhandelwal208
62 · AboveColin
59
Ask your house a question, get a number back. Home Assistant integration for TypeSafe Jev: typed answers as sensors, four actions for automations, and a conversation agent for Assist.
64 · harshitkhandelwal208
58
HK is a unified neural model format and framework built in native Zig, designed to replace SafeTensors, GGUF, and PyTorch checkpoints. Features zero-copy mmap loading, dual-mode quantization, 2:4 hardware sparsity, live model expansion, and 137+ architecture support with bindings for Python, Rust, Go, C#, Java, and TypeScript.
65 · whoashish115
57
A 777M-parameter Mixture-of-Experts language model trained from scratch for $55. Multi-head Latent Attention, DeepSeekMoE, own tokenizer.
70 · steverhysjenks
55
Logic-based multi-LLM voice router for Home Assistant, combining native intents, local Qwen, GPU-aware desktop Ollama, and cloud AI with intelligent fallback.