#esmfold2

Live, measured metrics for the hashtag #esmfold2 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
3
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 3
0
Avg reactions / post
Mastodon · last 3

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 14:12 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 14:12 UTC

No related tags with measured usage found for #esmfold2.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 14:12 UTC

Everything below is measured over the latest 3 public posts (spanning ~162 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (3)

Avg boosts / post: 0

Top of the latest posts

  • #KnowledgeByte: #ESMFold2 is an open-source, language-model-driven computational engine that utilizes pre-trained evolutionary representations to predict the 3D atomic structures of complex proteins, nucleic acids, and therapeutic binders w

    Knowledge Zone@[email protected]♥ 0↻ 02026-06-04 11:17 UTCView post →

  • Latent.Space (@latentspacepod) Biohub의 Protein World Model 관련 글로, ESMC-6B와 ESMFold2, 68억 개 단백질과 11억 개 구조를 학습한 대규모 생물학 모델을 소개한다. 항체 설계, SAE, 그리고 생물학도 언어모델처럼 스케일링될 수 있다는 관점을 다룬다. https://x.com/latentspacepod/status/2059773588593660119 #protei

    ainews@[email protected]♥ 0↻ 02026-05-28 16:51 UTCView post →

  • Alex Rives (@alexrives) Latent Space AI for Science 팟캐스트에서 단백질 언어모델, 생물학에서의 스케일링, 그리고 새 ESMFold2에 대해 논의한 내용. 바이오/생물학 분야에서 LLM식 스케일링이 어떻게 적용되는지와 최신 단백질 모델 동향을 다룬다. https://x.com/alexrives/status/2059796719831785793 #proteinlm #esmfold2 #biol

    ainews@[email protected]♥ 0↻ 02026-05-28 16:51 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/esmfold2