| license: mit |
| language: |
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| en |
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| zh |
| tags: |
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| medical |
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| multimodal |
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| routing |
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| RAG |
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| siglip |
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| 🧠 MANN-Engram-Router Weights |
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| Welcome to the official model hub for MANN-Engram! |
| MANN-Engram is an Edge-Cloud Multimodal Semantic Router designed to shield Cloud VLMs (Vision-Language Models) from "Information Tsunamis" in complex medical and high-noise scenarios. |
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| This repository hosts the custom Skew-Gaussian tensor routing weights required by the MANN-Engram SDK. |
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| 🔗 GitHub Repository: MANN-Engram GitHub (Replace with your link) |
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| 📦 What's in this Repository? |
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| To keep the installation footprint as light as possible, this repository only contains the custom routing core weights (the Skew-Gaussian compressor). |
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| The foundational multimodal encoder (google/siglip-so400m-patch14-384) is automatically handled and downloaded by the transformers library when you initialize the SDK. |
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| 📂 Directory Structure |
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| We provide language-specific routing weights to ensure the highest semantic extraction accuracy: |
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| 📁 en/ (English Version - Available Now) |
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| skew_model_v4full_en.pt: The core weights for the mann_engram_en Python SDK. |
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| 📁 zh/ (Chinese Version - Coming Soon) |
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| skew_model_v4full_zh.pt: Optimized for Chinese medical contexts and intent extraction. |
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| 🚀 Quick Start |
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| 1. Install the SDK |
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| Make sure you have installed the MANN-Engram SDK from our GitHub repository: |
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| # Clone the GitHub repo and install |
| pip install -e . |
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| 2. Download the Weights |
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| Download the skew_model_v4full_en.pt file from the en/ folder in this repository. We recommend placing it in a weights/ directory at the root of your project. |
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| 3. Initialize the Router |
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| from mann_engram_en.router import MANNEngramRouter |
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| # Initialize the router (Hardcore Local Privacy Mode) |
| router = MANNEngramRouter( |
| siglip_model_path="google/siglip-so400m-patch14-384", # Handled via Hugging Face automatically |
| ckpt_path="./weights/skew_model_v4full_en.pt", # The weight file from this repo |
| enable_local_intent=True, # Zero Data Leakage local extraction |
| local_intent_model="Qwen/Qwen2.5-0.5B-Instruct" |
| ) |
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| # Start purifying your messy clinical data and multimodal files! |
| results = router.process_session( |
| raw_chat_input="Doctor hurry up! I hit my head on the door yesterday... Check these lab reports.", |
| file_paths=["blood_test.pdf", "history.docx"], |
| image_paths=["head_ct.jpg", "leg_mri.jpg"], |
| top_p=0.85 |
| ) |
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| print(f"✅ Successfully extracted core evidence! Stats: {results['stats']}") |
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| 🛡️ License & Citation |
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| These weights are released under the MIT License. If you use MANN-Engram in your research or production, please consider citing our GitHub repository. |
