tegwick
a83ef0a79a
Classify freedom-intelligence for State Hub (agents domain), sync FI-WP-0001..0003 with hub IDs, enrich catalog entries with profile/SWOT, and pin the open-weight reserve to D:\vault\coulomb\freedom-intelligence\ with strategic S-tier policy.
81 lines
2.7 KiB
YAML
81 lines
2.7 KiB
YAML
id: nomic-ai__nomic-embed-text-v1.5__candidate
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status: candidate
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name: nomic-embed-text-v1.5
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org: nomic-ai
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source:
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kind: huggingface
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url: https://huggingface.co/nomic-ai/nomic-embed-text-v1.5
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revision: main
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model_card_url: https://huggingface.co/nomic-ai/nomic-embed-text-v1.5
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project_url: https://www.nomic.ai/
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license:
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spdx: Apache-2.0
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url: https://huggingface.co/nomic-ai/nomic-embed-text-v1.5
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allows_offline_retention: true
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allows_local_ops: true
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allows_fine_tune: true
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notes: ""
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profile:
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summary: "Lightweight open text embedder for A/B with BGE-M3 and long-context retrieval experiments."
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original_source: https://huggingface.co/nomic-ai/nomic-embed-text-v1.5
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use_cases:
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- "Secondary / A/B embedding path vs BGE-M3"
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- "English-heavy RAG with low resource cost"
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- "Long-context embedding experiments (per card capabilities)"
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- "Portable laptop offline search indexes"
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sweet_spots:
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- "Small footprint Apache embed"
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- "Fast iteration when re-embedding corpora often"
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- "Nomic tooling and Matryoshka-style dimension flexibility (per card)"
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not_ideal_for:
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- "Sole multilingual production embed without A/B (prefer BGE-M3 default)"
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- "Generation tasks"
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- "Code-only retrieval (prefer code embed if held)"
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capability_notes: >
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Compact Nomic text embedding model. Held as runnable dual-path to avoid
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single-vendor embed lock-in and to re-eval retrieval quality cheaply.
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Prefer current v2 text card at pull if clearly better.
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swot:
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strengths:
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- "Tiny, Apache-2.0, easy to re-run indexes"
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- "Diversifies embed dependency next to BGE-M3"
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weaknesses:
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- "May lose multilingual or domain A/B vs BGE-M3"
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- "Version churn (v1.5 vs v2) needs careful pin"
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opportunities:
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- "Dimension-reduced storage for large corpora"
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- "Hybrid ensembles (BGE + nomic signals)"
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threats:
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- "Becomes redundant if one embed wins all lab evals"
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- "Upstream rename/deprecation of v1.5"
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size:
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total_bytes: 0
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total_human: "<1 GB"
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hardware_class:
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min_vram_gb_q4: 1
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min_vram_gb_fp16: 1
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notes: "CPU-friendly"
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axes: [B]
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priority: high
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collection:
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approved_by: ""
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approved_at: null
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downloaded_at: null
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downloaded_by: ""
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storage_path: ""
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brief_refs:
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- research/2026-07-24-baseline-field-survey.md
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reason: "P0/R lightweight embed for A/B with BGE-M3; long-context text retrieval."
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tags: [tier-r, embedding, rag]
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companions:
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- BAAI__bge-m3__candidate
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notes: "If v2 text is preferred at collection time, update id/url and supersede this candidate."
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history:
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- at: "2026-07-24"
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event: nominated
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by: baseline-survey
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detail: "P0 recommendation from initial deep research."
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- at: "2026-07-24"
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event: profile_swot_added
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by: grok
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detail: "schema 0.2 profile + SWOT."
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