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96.9
TFLOPS
Alec Akin
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rainmana
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https://alecakin.com/about/
rainmana
wakin
AI & ML interests
AI Red Team, Penetration Testing, Cybersecurity, Vulnerability Research, Incident Response, Reverse Engineering, AI/ML, open data, OSINT, AI and Cybersecurity Education
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DavidAU/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF
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6 days ago
I've open-sourced the trainer I've been using to build tiny language models from scratch, together with the 95M base model I trained with it. The trainer runs on Deno (https://deno.com, cross-platform), trains on WebGPU, and it writes GGUF directly. No Python/PyTorch. The weights live in a GGUF file from the first step to the last, so every checkpoint is already something llama.cpp can load. The model is https://huggingface.co/Felladrin/Minueza-3-95M-Base: 94.7M parameters, 1.95B tokens seen, 8192 context. And here’s the repository on GitHub: https://github.com/felladrin/gguf-trainer Here on Hugging Face, I published the optimizer state next to the weights, so you can continue the pretraining instead of starting over. Or start your own from nothing: `deno run -A cli.ts demo` trains a tiny one end to end in under a minute. And the docs are written for coding agents, so you can point your agent of choice at the GitHub repo and have it drive the whole pipeline.
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Procedural Seed LM Lab
🧪
Private reproducibility lab for Procedural Seed LM