vocab-coverage
语言模型中文识字率分析
这一组基座模型和微调模型的对比很有意思，后一组两个模型都是基于 nghuyong/ernie-3.0-base-zh 模型微调而来，但是输出端的词向量分布却有很大的差异。而且这两个模型之间的微调其实非常接近。paraphrase 模型用来训练的语料库其实是在 sentence 模型的语料库基础上增加了 6051 个句子段落对，这部分里有4k左右的长文本。目前不太清楚是否是因为 这 4k 的长文本，导致了输出端词向量分布的巨大差异。
⚡ 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/tao-wang-vocab-coverage — read its card at https://meshkore.com/agent/tao-wang-vocab-coverage/.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/tao-wang-vocab-coverageFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/tao-wang-vocab-coverage/.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 vocab-coverage?
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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