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Vaultkeeper/Corpus-Callosum-1.5B

sourceHugging Faceapache-2.0updated 7mo agoView on Hugging Face
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<div align="center" style="display: flex; justify-content: center; align-items: center; gap: 40px; flex-wrap: wrap; margin: 2em 0;"> <img src="https://huggingface.co/Vaultkeeper/Corpus-Callosum-1.5b/resolve/main/Corpus-Callosum-logo.png" alt="Corpus-Callosum" width="400" style="max-height: 400px;" />

<div style="text-align: center;"> <h1 style="margin: 0; font-size: 2.8em; line-height: 1.1;">Corpus-Callosum </h1> <p style="margin: 8px 0 0; font-size: 1.4em; opacity: 0.9; font-weight: 500;">by VaultAI</p> </div>

<img src="https://huggingface.co/Vaultkeeper/ouroboros-next/resolve/main/vaultai-logo.png" alt="VAULTAI" width="300" style="max-height: 300px;" /> </div>

<div align="center" style="margin: 2em 0; padding: 25px; border: 1px solid #444; border-radius: 12px; background: linear-gradient(145deg, #0a0a0a, #141414); box-shadow: 0 10px 30px rgba(0,0,0,0.7);"> <h2 style="margin: 0; font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; color: #ffffff; letter-spacing: 3px; font-size: 1.6em; text-transform: uppercase;"> Deployment Status: <span style="color: #ff3333; animation: pulse 1.5s infinite;">UNRELEASED</span> </h2>

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<p style="margin: 0; font-size: 1.1em; color: #aaa; font-weight: 600; letter-spacing: 1px; text-transform: uppercase;"> <span style="color: #ffcc00;">[ PRE-ALPHA ]</span> SOVEREIGN-CODE & CORPUS-CALLOSUM | ARCHITECTING... </p>

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✅ Routing, Millisecond-Fast.

The "Central Nervous System" of the VaultAI ecosystem. Corpus-Callosum is not a chatbot; it is a high-speed intent classifier and traffic controller.

Engineered for millisecond latency, Corpus-Callosum is a 1.5B parameter Slerp Merge. It bridges the generalist comprehension of Qwen 2.5 Instruct with the syntax-sensitivity of Qwen 2.5 Coder. Its sole job is to analyze your prompt and decide which expert in your fleet is best equipped to handle it.

🧠 Architecture & Identity: The Traffic Cop

Corpus-Callosum is designed to run silently in the background of system RAM. By utilizing a 50/50 Spherical Linear Interpolation (Slerp), VaultAI has created a tiny but hyper-intelligent router that understands the difference between a request for lore and a request for code.

Key Routing Commands:

  • —[1] Creative/Abstract: Routes to Ouroboros-level creative reasoning.
  • —[2] Logic/Code: Routes to Sovereign-level execution engines.
  • —[3] Hybrid Relay: Triggers a multi-stage collaborative workflow between experts.

⚡ Performance & Efficiency

Corpus-Callosum is optimized to live entirely in CPU RAM, leaving 100% of your GPU VRAM available for the primary experts.

MetricSpeed (Prompt Processing)Hardware RequirementSystem Footprint
Latency< 50ms0% GPU VRAM~1.1 GB (Q4_K_M)
Model Size1.5B ParametersCPU/RAM OnlyLightweight Background Process

Standardized Accuracy Benchmarks

Benchmarks are currently queued to test classification accuracy.

BenchmarkFocus AreaAccuracyStatus
Intent ClassificationLogic vs CreativeTBD⏳ Pending Eval
MMLU (Micro)Knowledge RetentionTBD⏳ Pending Eval

Model Details

  • —Type: Classification Language Model (Slerp Merge)
  • —Base Architecture: Qwen 2.5 (1.5B)
  • —Merge Method: SLERP (Spherical Linear Interpolation)
  • —Blend Ratio:
  • —50% — Qwen2.5-1.5B-Instruct
  • —50% — Qwen2.5-Coder-1.5B-Instruct
  • —Tokenizer: Qwen 2.5 (1.5B Base)
  • —License: Apache 2.0

Why Corpus-Callosum?

  • —Zero Latency Orchestration: Doesn't waste time being polite. It reads, classifies, and hands off.
  • —VRAM Preservation: Designed specifically for users with limited VRAM who need to manage multi-model expert fleets.
  • —Embedded Directive: Metadata-overridden to ensure it never breaks its "one-token" output rule.

<div align="center" style="display: flex; justify-content: center; align-items: center; gap: 40px; flex-wrap: wrap; margin: 2em 0;"> <img src="https://huggingface.co/Vaultkeeper/ouroboros-next/resolve/main/vaultai-logo.png" alt="VAULTAI" width="100" style="max-height: 100px;" /> </div>