open-weights
Vynis-0.1-2b-instantmeru-base-open-ai-weightslora-experiments-quant-to-full-weightsGrogros-llama-2-7b-hf-weightsmark-std0.005-key0-ft-OpenMathInstructopencapybara-math-30b-lora-weightsGrogros-llama-2-7b-hf-weightsmark-std0.005-key0-ft-OpenMathInstruct-loraupdated-weightsfinetuned_lora_weights_openbiollm
open-weight-model-registry
Open-Weight Model Registry
Interactive registry and direct comparison for open-weight AI models
Open-Weight Model Registry is a data-driven Hugging Face Space for exploring and directly comparing downloadable AI models across:
license
access status
architecture
parameter count
context length
modalities
self-hosting
commercial-use status
modification and redistribution status
documented runtimes
verification date
The Space reads from:… See the full description on the dataset page: https://huggingface.co/datasets/open-weights/open-weight-model-registry.open-weights-archiving-playbook
The Open-Weights Archiving Playbook
A practical, hard-won guide to keeping open-weight models offline — for independence, reproducibility, and peace of mind.
Part 1 of The Open-Weights Lifecycle — see roadmap.md for the full series arc (and article.md for the short story-version).
Why this exists. Open weights can disappear: providers deprecate repos, licenses change, geopolitics tightens export rules, or an API you depend on simply gets turned off. If a model matters to you… See the full description on the dataset page: https://huggingface.co/datasets/AXOlotlvaNschmozelot/open-weights-archiving-playbook.run-open-weights-locally
Run your first local open-weights model in 5 minutes
Part 3 of The Open-Weights Lifecycle — acquire → verify → run → maintain → retire.
You've acquired a model (Part 1) and worked out which quant fits your machine (Part 2). Now the fun part: actually running it — on your own hardware, offline, no API key, no monthly bill.
The surprise most people don't expect: you don't need a big GPU, or any GPU at all. A mainstream laptop runs small models comfortably on the CPU alone. Here's… See the full description on the dataset page: https://huggingface.co/datasets/AXOlotlvaNschmozelot/run-open-weights-locally.retire-open-weights
Let it go — retiring an open-weights model with dignity
Part 5 of The Open-Weights Lifecycle — acquire → verify → run → maintain → retire.
Every guide about archiving tells you how to keep things. Almost none tell you how to stop keeping something — and that's the habit that separates a curated library from a hoard. A healthy archive isn't the one that never deletes; it's the one that deletes on purpose.
This is the part of the lifecycle nobody writes about. So here it is: how… See the full description on the dataset page: https://huggingface.co/datasets/AXOlotlvaNschmozelot/retire-open-weights.keep-open-weights-alive
Keep your local model library alive
Part 4 of The Open-Weights Lifecycle — acquire → verify → run → maintain → retire.
You downloaded the models (Part 1), sized them (Part 2), and ran them (Part 3). But an archive is not a "set it and forget it" thing. Files rot, disks die, and future-you forgets what half the folders even are. Keeping a library alive is a little bit of light maintenance, done on a rhythm — not a big project.
Here are the five habits that keep a local model… See the full description on the dataset page: https://huggingface.co/datasets/AXOlotlvaNschmozelot/keep-open-weights-alive.