AL
ENT-00001631 · Modèle IA

All-mpnet-base-v2

All-mpnet-base-v2 is a AI model associated with Sentence Transformers, classified in LXKeys.world as Embedding / Retrieval Model.

Niveau IV ConnectéActifDocumenté
Fiche publique

Vue d’ensemble

All-mpnet-base-v2 is a AI model associated with Sentence Transformers. This Entry records its public identity, classification as Embedding / Retrieval Model, source provenance, release or appearance history, documented capabilities and graph relationships. Primary-source material is preferred for factual maintenance; secondary references are retained only as supporting context.

Chronologie

  1. 2023Initial model publication or release

    All-mpnet-base-v2 entered the documented public record in 2023. This event is retained at the precision supported by the Entry’s reviewed source history.

Capacités

Semantic embeddingRetrieval supportSimilarity search

Limites connues

Capabilities and behavior depend on the specific model version, checkpoints, prompting, tools and deployment configuration.Performance claims should be interpreted against the documented evaluation protocol and source material rather than generalized across tasks.Availability, licensing, safety controls and supported modalities may change over time.
Détail technique et structuré

Description technique

Structured LXKeys.world registry record for All-mpnet-base-v2. Entity type: AI Model; classification: Embedding / Retrieval Model; creator/organization context: Sentence Transformers. Canonical source anchor: https://huggingface.co/sentence-transformers/all-mpnet-base-v2. The record tracks source authority, first public appearance, timeline, capabilities, limitations, registry status and graph relationships. Automatic refresh is limited to sources explicitly classified as OFFICIAL and enabled for updates; documentary and research references remain non-authoritative unless reviewed.

Tags contrôlés

EmbeddingRetrievalAI Model
Graphe relationnel

All-mpnet-base-v2

Ouvrir dans le graphe complet
All-mpnet-base-v2
Créé parSortante
Sentence Transformers

All-mpnet-base-v2 is associated with Sentence Transformers through its documented source context.

Couche lisible par machine

Données structurées de l’entrée pour les outils humains, les systèmes IA et les clients machine.

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    "@type": "Thing",
    "identifier": "ENT-00001631",
    "name": "All-mpnet-base-v2",
    "alternateName": [],
    "additionalType": {
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    "description": "All-mpnet-base-v2 is a AI model associated with Sentence Transformers, classified in LXKeys.world as Embedding / Retrieval Model.",
    "creator": "Sentence Transformers",
    "url": "https://lxkeys.world/entry.php?id=ENT-00001631&lang=fr",
    "sameAs": "https://huggingface.co/sentence-transformers/all-mpnet-base-v2",
    "image": "",
    "lxkeysWorld": {
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        "classification": "Embedding / Retrieval Model",
        "organization": "Sentence Transformers",
        "originContext": "Public AI and technical record",
        "firstPublicAppearance": "2023",
        "currentStatus": "Active",
        "documentationStatus": "Documented",
        "documentationIndex": {
            "total": 74,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 11,
            "level": "Level IV Connected"
        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-16T23:59:28+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "updated_utc": "2026-06-16T23:59:28+00:00",
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        "facts": [],
        "capabilities": [
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            "Performance claims should be interpreted against the documented evaluation protocol and source material rather than generalized across tasks.",
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                "date": "2023",
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                "description": "All-mpnet-base-v2 entered the documented public record in 2023. This event is retained at the precision supported by the Entry’s reviewed source history.",
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        "relationships": [
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                "type": "Created by",
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        "sources": [
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}
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