#modelcompression

Live, measured metrics for the hashtag #modelcompression from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

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0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
14
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 14
0
Avg reactions / post
Mastodon · last 14

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 05:32 UTC
0
07-21
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27

0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-27 05:32 UTC

No related tags with measured usage found for #modelcompression.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 05:32 UTC

Everything below is measured over the latest 14 public posts (spanning ~32434 hours).

Posting hours (UTC) — busiest: 21:00

00:0012:0023:00

Languages: English (14)

Avg boosts / post: 0.1

Top of the latest posts

  • Avi Chawla (@_avichawla) 좁은 작업에 맞춰 모델 파라미터를 줄이는 방식으로, 자체 호스팅 AI 모델 비용을 약 75% 낮출 수 있다는 주장이다. 예를 들어 리랭커는 범용 세계지식 전체가 필요하지 않으므로, 작업과 무관한 파라미터를 제거·경량화해 추론 비용과 메모리 사용량을 줄일 수 있다는 접근을 제시한다. https://x.com/_avichawla/status/2078746543847579984 #self

    ainews@[email protected]♥ 0↻ 12026-07-19 18:51 UTCView post →

  • Alis volat propriis (@Alisvolatprop12) GLM-5.2 504B를 참고해 GLM-5.2의 파라미터를 더 줄이는 양자화 실험을 진행하려는 내용입니다. MXL 기반으로 모델 크기를 더 줄이면서 품질을 유지하거나 개선하려는 방향으로, 경량화·배포 최적화에 관심 있는 개발자에게 실용적인 힌트입니다. https://x.com/Alisvolatprop12/status/2076130793806852456 #qu

    ainews@[email protected]♥ 0↻ 02026-07-12 13:45 UTCView post →

  • Yuval Avidani (יובל אבידני) (@yuvalav) Unsloth를 소개하는 트윗으로, 로컬에서 무료로 모델을 더 작게 만들어 일반적인 PC에서도 실행 가능하게 해준다고 설명한다. 또한 최근 Unsloth Studio를 출시했다는 점을 언급하며, 로컬 모델 실행·경량화 도구로서의 가치를 강조한다. https://x.com/yuvalav/status/2069099004449726604 #unsloth #loca

    ainews@[email protected]♥ 0↻ 02026-06-23 03:54 UTCView post →

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/modelcompression