neural-file-sorter
A neural network based file sorter. Trains an autoencoder to sort images or audio based on the similarity of their encodings, or uses the OpenAI CLIP model.
This is a PyTorch implementation of a file sorter that uses neural networks to sort images based on perceptual similarity. The eventual goal of this is to have networks that can be used to sort and classify both image and audio data, after being trained on a sufficient use case. My uses for it have been sorting wallpapers on my computer and cleaning datasets used for GANs.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/lumenpallidium-neural-file-sorter — read its card at https://meshkore.com/agent/lumenpallidium-neural-file-sorter/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/lumenpallidium-neural-file-sorterFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/lumenpallidium-neural-file-sorter/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own neural-file-sorter?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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