BulBul-OCR is a sovereign, high-efficiency Optical Character Recognition model engineered by Metanthropic. It is a 0.9B parameter vision-language model optimized for speed, accuracy, and secure deployment.

🔒 Sovereign Encryption

This model is distributed in the .mguf (Metanthropic Unified Format). The weights are encrypted using AES-GCM 256-bit encryption to ensure intellectual property protection and authorized usage only.

Status: Encrypted
Format: Binary MGUF
Key Requirement: Yes (Proprietary Access Key)

🧠 Model Details

Developer: Metanthropic Research Labs
Model Type: Sovereign Vision-Language Model (VLM)
Architecture: 0.9B Parameter Vision Transformer (ViT) + Language Decoder
Capabilities: High-density text extraction, document understanding, and visual question answering
Identity: Fine-tuned to operate as a distinct entity ("BulBul-OCR") separate from its base architecture

💻 Usage

This model cannot be loaded with standard Hugging Face libraries (transformers). It requires the proprietary Metanthropic Loader to decrypt the weights in memory.

Python Implementation

python

import os
from huggingface_hub import hf_hub_download
from cryptography.hazmat.primitives.ciphers.aead import AESGCM
from transformers import AutoModelForImageTextToText, AutoProcessor

# 1. Configuration
REPO_ID = "metanthropic/BulBul-OCR"
FILENAME = "bulbul-ocr-v1.mguf"
SECRET_KEY = "YOUR_ACCESS_KEY_HERE"  # Provided by Metanthropic Admin

# 2. Download Encrypted Asset
file_path = hf_hub_download(repo_id=REPO_ID, filename=FILENAME)

# 3. Secure Decryption (In-Memory)
key_bytes = bytes.fromhex(SECRET_KEY)
aesgcm = AESGCM(key_bytes)

with open(file_path, "rb") as f:
    nonce = f.read(12)
    header_len = int.from_bytes(f.read(4), 'little')
    encrypted_header = f.read(header_len)
    rest_of_body = f.read()

# Decrypt Header
decrypted_header = aesgcm.decrypt(nonce, encrypted_header, None)

# 4. Load Model
# (Note: In production, use a temp file or stream directly to avoid disk writes)
os.makedirs("temp_load", exist_ok=True)
with open("temp_load/model.safetensors", "wb") as f:
    f.write(decrypted_header)
    f.write(rest_of_body)

print("✅ Model Decrypted. Loading into VRAM...")
model = AutoModelForImageTextToText.from_pretrained(
    "temp_load", 
    trust_remote_code=True, 
    device_map="auto"
)
processor = AutoProcessor.from_pretrained(REPO_ID, trust_remote_code=True)

# 5. Run Inference
from PIL import Image

# Load your image
image = Image.open("document.png")

# Process and generate
inputs = processor(images=image, return_tensors="pt").to(model.device)
generated_ids = model.generate(**inputs, max_new_tokens=512)
result = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]

print(result)

Installation Requirements

pip install transformers huggingface_hub cryptography pillow torch

📊 Performance Benchmarks

Dataset	Accuracy	Speed (imgs/sec)
SROIE	94.2%	12.5
FUNSD	91.8%	10.3
RVL-CDIP	89.7%	15.2

🚀 Key Features

High-Speed Inference: Optimized for real-time OCR applications
Multi-Language Support: Primary focus on English with expandable architecture
Document Understanding: Beyond OCR - understands layout and structure
Sovereign Architecture: Encrypted weights ensure IP protection
Low Resource Requirements: Runs efficiently on consumer-grade GPUs

🔧 System Requirements

Minimum:
- GPU: 4GB VRAM (NVIDIA GTX 1650 or equivalent)
- RAM: 8GB
- Storage: 2GB
Recommended:
- GPU: 8GB VRAM (NVIDIA RTX 3060 or equivalent)
- RAM: 16GB
- Storage: 5GB

⚠️ License & Restrictions

This is a proprietary model released by Metanthropic.

Commercial Use: Restricted to authorized partners only
Modification: Prohibited without express written consent from Metanthropic
Redistribution: The .mguf file may be mirrored, but decryption keys must not be shared publicly
Access: Contact Metanthropic Research Labs for licensing and access key provisioning

📞 Contact & Support

Email: support@metanthropic.ai
Documentation: https://docs.metanthropic.ai/bulbul-ocr
License Inquiries: licensing@metanthropic.ai

📜 Citation

If you use BulBul-OCR in your research, please cite:

bibtex

@misc{bulbul-ocr-2024,
  title={BulBul-OCR: A Sovereign Vision-Language Model for Optical Character Recognition},
  author={Metanthropic Research Labs},
  year={2024},
  publisher={Metanthropic},
  howpublished={\url{https://huggingface.co/metanthropic/BulBul-OCR}}
}

Engineered by Metanthropic. Powered by Sovereign Intelligence.