Dontopedia

hf

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)

hf has 22 facts recorded in Dontopedia across 18 references, with 2 live disagreements.

22 facts·11 predicates·18 sources·2 in dispute

Mostly:rdf:type(7), hosts outdated checkpoints(1), source of models and datasets(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (31)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

hostedOnHosted on(8)

providedByProvided by(2)

affiliatedWithPlatformAffiliated With Platform(1)

areHostedOnAre Hosted on(1)

associatedDataLocationAssociated Data Location(1)

cachedByCached by(1)

canBeDeployedToHfCan Be Deployed to Hf(1)

fromHuggingfaceFrom Huggingface(1)

hostedByHosted by(1)

hostsModelOnHosts Model on(1)

implementedStreamingImplemented Streaming(1)

involvesInvolves(1)

locatedOnLocated on(1)

mentionsMentions(1)

mentionsPlatformMentions Platform(1)

moreUpToDateThanMore Up to Date Than(1)

plansDataOnPlans Data on(1)

plansHFdatasetPlans H Fdataset(1)

prefersHuggingfaceForDataPrefers Huggingface for Data(1)

publishedOnPublished on(1)

referencesHuggingfaceModelsReferences Huggingface Models(1)

referencesHuggingfacePlatformReferences Huggingface Platform(1)

solvedStreamingIssueSolved Streaming Issue(1)

Other facts (17)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

17 facts
PredicateValueRef
Rdf:typeOrganization[10]
Rdf:typePlatform[11]
Rdf:typePlatform[12]
Rdf:typePlatform[13]
Rdf:typeOrganization[14]
Rdf:typePlatform[15]
Rdf:typePlatform[18]
Hosts Outdated CheckpointsModel Checkpoints[1]
Source of Models and Datasetsnull[2]
Source of DatasetsSpeaking Model[3]
Added Hot Weight Reload Endpointtrue[4]
Abbreviated As Hfhf[5]
Has Replaceable Layertrue[6]
ML Librarytrue[6]
Caches Datasetsnull[7]
Provides Tokenizers CrateTokenizers Crate[8]
Hosts Benchmarksnull[9]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

hostsOutdatedCheckpointsblah/posers/part-3
ex:model-checkpoints
sourceOfModelsAndDatasetsblah/training-and-evals/part-1
null
sourceOfDatasetsblah/training-and-evals/part-2
ex:speaking-model
addedHotWeightReloadEndpointblah/training-and-evals/part-7
true
abbreviatedAsHfblah/training-and-evals/part-30
hf
hasReplaceableLayerblah/training-and-evals/part-29
true
mlLibraryblah/training-and-evals/part-29
true
cachesDatasetsblah/watt-activation/part-244
null
providesTokenizersCrateblah/watt-activation/part-485
ex:tokenizers-crate
hostsBenchmarksblah/models/part-5
null
typebeam/237ebfc7-75b0-4074-93e7-2a0904cef572
ex:Organization
labelbeam/237ebfc7-75b0-4074-93e7-2a0904cef572
Hugging Face
typeblah/models/5
ex:Platform
typeblah/posers/3
ex:Platform
labelblah/posers/3
hf
typeblah/resources/20
ex:Platform
typeblah/resources/42
ex:Organization
typeblah/training-and-evals/4
ex:Platform
labelblah/watt-activation/1
Hugging Face
labelblah/watt-activation/178
Hugging Face
typeblah/watt-activation/243
ex:Platform
labelblah/watt-activation/243
HuggingFace

References (18)

18 references
  1. [1]Part 31 fact
    ctx:discord/blah/posers/part-3
  2. [2]Part 11 fact
    ctx:discord/blah/training-and-evals/part-1
  3. [3]Part 21 fact
    ctx:discord/blah/training-and-evals/part-2
  4. [4]Part 71 fact
    ctx:discord/blah/training-and-evals/part-7
  5. [5]Part 301 fact
    ctx:discord/blah/training-and-evals/part-30
  6. [6]Part 292 facts
    ctx:discord/blah/training-and-evals/part-29
  7. [7]Part 2441 fact
    ctx:discord/blah/watt-activation/part-244
  8. [8]Part 4851 fact
    ctx:discord/blah/watt-activation/part-485
  9. [9]Part 51 fact
    ctx:discord/blah/models/part-5
  10. ctx:claims/beam/237ebfc7-75b0-4074-93e7-2a0904cef572
    • full textbeam-chunk
      text/plain1 KBdoc:beam/237ebfc7-75b0-4074-93e7-2a0904cef572
      Show excerpt
      By preparing thoughtful responses to potential questions and demonstrating how you plan to integrate and manage Solr 9.1.0 in your RAG system, you can effectively address stakeholder concerns and refine your technology choices based on thei
  11. [11]51 fact
    ctx:discord/blah/models/5
    • full textmodels-5
      text/plain3 KBdoc:agent/models-5/a4fe41e4-9834-4a41-b9f9-a98d44341b57
      Show excerpt
      [2025-04-06 12:35] ajaxdavis: https://thomasalwyndavis--example-axolotl-inference-web.modal.run/?input=what%20is%20resumed%20cli [2025-04-06 12:40] ajaxdavis: https://v0-mood-based-webpage-wbdhsn.vercel.app/ [2025-04-06 12:41] foxhop.: Sup
  12. [12]32 facts
    ctx:discord/blah/posers/3
    • full textposers-3
      text/plain2 KBdoc:agent/posers-3/a94b5ebd-419a-4892-b144-1e6ddf719339
      Show excerpt
      [2026-01-17 05:34] lisamegawatts: and store the models and animations, it chose strange db but justified it so i am rolling with it [2026-01-19 01:27] traves_theberge: <@1211062099137265723> Hows this coming along? [2026-01-19 01:59] lisa
  13. [13]201 fact
    ctx:discord/blah/resources/20
    • full textresources-20
      text/plain3 KBdoc:agent/resources-20/e9723ab5-11f7-415c-b21e-7b97e84bb7b2
      Show excerpt
      [2025-11-25 02:07] optionalsecurity: I'll take a look at the workflow builder [2025-11-25 05:38] traves_theberge: https://github.com/oxylabs/google-ai-mode-scraper [2025-11-25 06:13] ajaxdavis: my brain cannot parse what this description sa
  14. [14]421 fact
    ctx:discord/blah/resources/42
    • full textresources-42
      text/plain3 KBdoc:agent/resources-42/ab63ab41-f427-4d03-afa9-3acb6dc41ffa
      Show excerpt
      [2026-02-22 05:21] traves_theberge: used GLM-5 to write the whole thing O.o its actually really good lol [2026-02-22 05:21] traves_theberge: i suppose my custom agents and skills helped it along a little but damn. [2026-02-22 15:53] traves_
  15. [15]41 fact
    ctx:discord/blah/training-and-evals/4
    • full texttraining-and-evals-4
      text/plain3 KBdoc:agent/training-and-evals-4/cbd9138e-7287-420c-8010-0f199e43ea51
      Show excerpt
      [2026-02-18 08:07] lisamegawatts: checking out open router this is the coding benchmark they are using, https://www.tbench.ai/ " Terminal-Bench 2.0: a carefully curated hard benchmark composed of 89 tasks in computer terminal environments i
  16. [16]11 fact
    ctx:discord/blah/watt-activation/1
    • full textwatt-activation-1
      text/plain3 KBdoc:agent/watt-activation-1/83ab6e73-1b84-4a84-b9fe-e21a39a0ff4c
      Show excerpt
      [2026-02-25 21:08] lisamegawatts: Tell Claude to use the gelation signal to avoid overfitting to training data, it is a reliable indicator and gives a distinct early signal that can be detected [2026-02-25 21:11] ajaxdavis: https://klipy.co
  17. [17]1781 fact
    ctx:discord/blah/watt-activation/178
    • full textwatt-activation-178
      text/plain3 KBdoc:agent/watt-activation-178/50ec323b-637a-4c18-bba8-73839dc1355d
      Show excerpt
      [2026-03-10 00:29] xenonfun: ⏺ That settles it — the base instruct model has no factual knowledge at all. It generates fluent-sounding nonsense rather than facts. This is a pretraining depth problem: FineWeb-Edu teaches language patterns,
  18. [18]2432 facts
    ctx:discord/blah/watt-activation/243
    • full textwatt-activation-243
      text/plain3 KBdoc:agent/watt-activation-243/14f8ddd1-c20c-4aa1-99ee-73dc849eba12
      Show excerpt
      [2026-03-12 05:04] xenonfun: ⏺ While we wait for the image data to re-prep, let me summarize the issues found and fixed: Problems found: 1. tok/s inflated — was averaging all modality step times but computing tokens as bs*seq which onl

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