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.
82 lines
2.9 KiB
YAML
82 lines
2.9 KiB
YAML
id: meta-llama__Llama-3.2-3B-Instruct__candidate
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status: candidate
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name: Llama-3.2-3B-Instruct
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org: meta-llama
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source:
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kind: huggingface
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url: https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct
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revision: main
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model_card_url: https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct
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project_url: https://www.llama.com/
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license:
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spdx: custom
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url: https://ai.meta.com/llama/license/
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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: "Llama Community License — not MIT; review terms before commercial redistribution."
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profile:
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summary: "Tiny edge instruct for always-on and low-VRAM agent micro-services."
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original_source: https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct
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use_cases:
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- "Always-on local helper with minimal power/VRAM"
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- "Fast classification, routing, and short-form rewrites"
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- "CPU or 4–8 GB GPU edge boxes"
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- "Smoke-test harnesses before promoting to 8B+"
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- "Embedded tooling demos and offline kiosks"
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sweet_spots:
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- "Latency and footprint over peak intelligence"
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- "Huge Llama ecosystem (llama.cpp, Ollama, many templates)"
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- "Cheap parallel micro-agents in a fleet"
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not_ideal_for:
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- "Serious coding or long documents"
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- "Domain FT when quality matters (prefer 8B base)"
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- "Standalone reasoning-heavy ops decisions"
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capability_notes: >
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Compact Meta instruct model. Best as a floor for local intelligence and
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high-volume simple tasks, not as the lab's primary brain.
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swot:
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strengths:
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- "Very small; runs almost anywhere in the lab"
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- "Massive tooling and community template coverage"
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- "Good enough for structured short outputs"
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weaknesses:
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- "Shallow capability; fails hard tasks silently if not constrained"
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- "Custom Llama license (not pure OSS-permissive)"
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- "HF gated access friction"
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opportunities:
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- "Fleet of specialized tiny adapters per workflow"
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- "Guardrail / router model in front of larger backends"
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threats:
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- "Qwen/Gemma/Smol peers may outclass at same size"
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- "License or regional policy changes for Llama family"
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size:
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total_bytes: 0
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total_human: "~6 GB fp16 / ~2 GB Q4 (estimate)"
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hardware_class:
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min_vram_gb_q4: 3
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min_vram_gb_fp16: 8
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notes: "T0–T1 edge / always-on"
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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 edge instruct — tiny, huge ecosystem, good CPU/GPU floor for agents."
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tags: [tier-r, instruct, edge, llama]
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companions: []
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notes: "HF gated model — need accepted license on account before download."
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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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