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Dorman11
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AI & ML interests

Currently training Endeavor, a SLM model! Interests include: Agentic security, Machine Learning, Reinforcement Learning, PyTorch and all around web dev ninja! Level II Specialist working in Cyber Security field.

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updated a Space about 2 hours ago
Dorman11/open-mythos-run
updated a bucket about 2 hours ago
Dorman11/datasetdb
reacted to maglun's post with 🚀 1 day ago
I work on quantizing models to run efficiently on local hardware, and kept being curious how existing quants spend their "bit budget" during optimization and built a local tool to explore. Many quants apply one setting across all tensors, but some do more interesting things: the model in the screenshot holds attention K at 4.5 bits while Q/V/O get 8.5, and protects layer 0 MLP. It turned out useful enough that I made it public: https://tensorlens.dev Explore any HF model in the browser without downloading it. The anatomy map is read from the safetensors header via a range request, and only tensors you click ever stream. Large tensors are sampled rather than streamed in full. Limitations: safetensors only (no GGUF yet), some exotic variants don't work yet, and gated repos aren't supported yet. Feedback very welcome, especially models that break it.
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