#模型訓練
Live, measured metrics for the hashtag #模型訓練 from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #模型訓練
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · mastodon.online (Mastodon public tags API) · fetched 2026-08-23 10:53 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.online (Mastodon public search API) · fetched 2026-08-23 10:53 UTCLive pulse
measured · mastodon.online (Mastodon tag timeline) · fetched 2026-08-23 10:53 UTCEverything below is measured over the latest 22 public posts (spanning ~26301 hours).
Posting hours (UTC) — busiest: 15:00
Languages: Chinese (Taiwan) (18) · Chinese (4)
Avg boosts / post: 0
Top of the latest posts
🌗 高威一間書店收到 5,000 本冷門書籍的「瘋狂」訂單，引發外界懷疑 ➤ 實體書淪為 AI 燃料：科技巨頭暗中掃貨的數位化侵權爭議 ✤ https://www.irishtimes.com/world/europe/2026/08/10/a-mysterious-buying-spree-is-unsettling-europes-booksellers/ 歐洲獨立書店近期陸續收到大量且不合常理的冷門書籍訂單，引發業界懷疑。這些訂單疑似由科技巨頭利用 AI 機器人自動下
🌗 GitHub - MakazhanAlpamys/Soup：讓大型語言模型微調告別繁瑣流程，單一配置與指令即可完成 ➤ 從基礎設施地獄到一鍵訓練：Soup 重新定義 LLM 開發流程 ✤ https://github.com/MakazhanAlpamys/Soup Soup 是一款專為簡化大型語言模型（LLM）微調與訓練流程而設計的開源工具，旨在解決開發者在管理 GPU 基礎設施與複雜配置時的痛點。該工具透過「層級串流」（Layer Streaming）技術，將模型基
🌘 將 nanochat 移植至 TPU：從 PyTorch 遷移的繼承與挑戰 ➤ 邁向「百元速成」：在 TPU v6e 上重現全端 LLM 訓練 ✤ https://github.com/tucan9389/nanochat-jax/discussions/1 本文記錄了將 Karpathy 的 nanochat 全端大型語言模型專案從 PyTorch 移植至 Google TPU（v6e-8）的技術過程。作者旨在維持與原版 nanochat 相同的架構與配置，並成功重現
#模型訓練 across platforms
every network with a public tag surfaceFollow #模型訓練 straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/模型訓練