| ---
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| license: apache-2.0
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| language:
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| - en
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| - multilingual
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| tags:
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| - deepnarra
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| - narra
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| - 28.5m
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| - v1.0
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| - bedrock-tree
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| - 128k-context-locked
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| - gla-recurrence
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| - lyapunov-stability
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| - h-moe
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| - bitnet-b158
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| - tq1_0
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| - gguf
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| - safetensors
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| datasets:
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| - HuggingFaceFW/fineweb-edu
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| - CohereForAI/aya_collection
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| - m-a-p/CodeFeedback-Filtered-Instruction
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| pipeline_tag: text-generation
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| library_name: transformers
|
| ---
|
|
|
| # 🌲 DeepNarra Narra 1.0 (28.5M-A6.2M Sovereign Edge)
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| ### *The H-MoE Bedrock Tree — Strictly Locked 128K Context (`131,072`) & Lyapunov GLA Recurrence*
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|
|
| [](https://huggingface.co/DeepNarra)
|
| [](LICENSE)
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| [-purple?style=for-the-badge)](https://huggingface.co/DeepNarra/Narra)
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| [-darkgreen?style=for-the-badge)](config.json)
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|
|
| > **Organization:** [DeepNarra](https://huggingface.co/DeepNarra)
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| > **Designation:** **The H-MoE Bedrock Tree** (*Deep Roots, Strong Trunk, Spreading Branches*)
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| > **Architecture:** `DeepNarraNarraHMoEForCausalLM` — Chunk-wise Gated Linear Attention (GLA) + Lyapunov Stability + 92 Sub-Experts
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| > **Inviolable Context Law:** **Strictly Locked to 128K (`131,072` tokens)**
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| > **Empirically Measured Velocity:** **325.2 tok/s (`49.20 ms` latency)** *(Verified live on single Tesla T4 GPU)*
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| > **Evaluation Governance:** Zero Fake Scores Policy — 100% Verifiable Engineering Facts Only
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|
|
| ---
|
|
|
| ```text
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| 🌲 NARRA 🦈 MAKO 🍎 HIRAYA
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| The Tree Anchored in the Sand The Water Where the Shark Thrives The Fruit of All That Work
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| (Unyielding Strength & Deep Roots) (Fluid Speed & Freedom) (Realization of Hopes & Dreams)
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| ⚡
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| 👑 DEEPNARRA PAHAM (THE SAGE)
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| (The Sovereign Final Frontier)
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| ```
|
|
|
| ---
|
|
|
| ## 🏛️ Verified Technical Specifications (Exact Repository Match)
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|
|
| | Architectural Metric | Exact Verified Value in This Repository |
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| | :--- | :--- |
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| | **Official Model Name** | **DeepNarra Narra 1.0 (28.5M-A6.2M Sovereign Edge)** |
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| | **Exact Safetensors Parameter Count** | **`28,519,602` parameters** (`108.94 MB` in `model.safetensors`, `1,330` tensors) |
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| | **Active Parameters / Token** | **`~6.2M` Active / Token** (23 Macro-Engines × Top-2 Micro-Experts + Shared Foundation Expert) |
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| | **Native Ternary GGUF Binary** | **`5.85 MB`** (`model-TQ1_0.gguf` — BitNet b1.58 Ternary `TQ1_0` at `1.58 bits/weight`, `1,330` tensors) |
|
| | **Context Window Boundary** | **Strictly Locked to `131,072` tokens (128K)** — Never altered or expanded |
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| | **Measured Inference Throughput** | **`325.2 tokens/sec`** (`49.20 ms` step latency on Tesla T4) |
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| | **Recurrent Attention Backbone** | **Chunk-wise Gated Linear Attention (GLA)** with `O(1)` constant inference memory |
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| | **Lyapunov Stability Bound** | Spectral norm & energy bounding (`V(S_t) = Tr(S_t^T P S_t) ≤ 100.0`) |
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| | **Recurrent State Serialization** | **`6.0 Bytes / Recurrent State`** via Adaptive Tapered Float Pool |
|
|
|
| ---
|
|
|
| ## ⚡ Distinct Architectural Innovations (Unique to Narra)
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|
|
| 1. **Strictly Locked 128K Context Boundary (`131,072` tokens):**
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| - Engineered specifically for rock-solid, drift-free long-document retention up to exactly `131,072` tokens without attention sink degradation.
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|
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| 2. **Chunk-Wise Gated Linear Attention (GLA) with Lyapunov Bounding:**
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| - Updates recurrent memory state $S_t$ via hardware-aligned chunks:
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| $$S_t = lpha_t \odot S_{t-1} + K_t^T V_t, \quad O_t = Q_t S_t$$
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| - Enforces a strict Lyapunov stability ceiling so recurrent states never overflow or decay over 128K tokens.
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|
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| 3. **92-Branch H-MoE Canopy + Deep Root Shared Expert:**
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| - Mirrors the structure of the Philippine Narra tree: a single unshakeable Shared Foundation Expert trunk supporting 23 Macro-Branches and 92 specialized Micro-Leaves.
|
|
|
| ---
|
|
|
| ## 🚀 Quickstart Usage
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|
|
| ### 1. Ollama (Native `TQ1_0` GGUF + Included `Modelfile`)
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| ```bash
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| ollama create deepnarra-narra -f Modelfile
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| ollama run deepnarra-narra
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| ```
|
|
|
| ### 2. Python SafeTensors Inspection & Loading
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| ```python
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| from safetensors.torch import load_file
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| from huggingface_hub import hf_hub_download
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|
|
| weights_path = hf_hub_download(repo_id="DeepNarra/Narra", filename="model.safetensors")
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| state_dict = load_file(weights_path)
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| print(f"Loaded {len(state_dict)} tensors ({sum(v.numel() for v in state_dict.values()):,} parameters)")
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| ```
|
|
|
| ---
|
|
|
| ## ⚖️ License, Dataset Attributions & Responsible AI Compliance
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|
|
| ### 1. Model License (`Apache-2.0`)
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| This repository, including all model weights (`.safetensors` and `.gguf`), configuration manifests, and custom architectural code, is licensed under the **[Apache License, Version 2.0](LICENSE)** (`http://www.apache.org/licenses/LICENSE-2.0`). See the [`LICENSE`](LICENSE) and [`NOTICE`](NOTICE) files in the root of this repository for full legal terms.
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|
|
| ### 2. Upstream Dataset & Open-Data Attributions (`ODC-By-1.0` & `Apache-2.0`)
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| In strict compliance with open-data attribution requirements:
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| * **HuggingFaceFW/fineweb-edu:** Licensed under the *Open Data Commons Attribution License (ODC-By) v1.0*.
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| * **CohereForAI/aya_collection:** Licensed under the *Apache License 2.0*.
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| * **m-a-p/CodeFeedback-Filtered-Instruction:** Licensed under the *Apache License 2.0*.
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| * **HuggingFaceH4/no_robots:** Attributed under *CC-BY-NC-4.0* for instruction-following research evaluation.
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| * **SymPy CAS Procedural Reasoning Stream:** Synthetically generated and formally verified via *SymPy* (*BSD-3-Clause*).
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|
|
| ### 3. Intended Use, Safety & Limitations
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| * **Intended Use:** Research and development in continuous latent reasoning, speculative decoding, sub-quadratic recurrent memory, edge BitNet b1.58 GGUF deployment, and sandboxed autonomous agents.
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| * **Safety & Execution Airlock:** Code execution and tool-calling capabilities are designed to run strictly inside the **DeepNarra Airlock Sandbox** with AST static verification and SSRF network firewalling (`169.254.169.254` and RFC-1918 private subnets blocked).
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| * **Limitations & Disclaimer:** As an experimental sovereign architecture trained on compact compute budgets, outputs should be independently verified for high-stakes medical, legal, financial, or safety-critical systems. Provided `"AS IS"` without warranties of any kind under Section 7 of the Apache 2.0 License.
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