Ken1.0-67B - Russian Legal AI Model

Ken1.0-67B is a specialized large language model (67 billion parameters) engineered for the Russian legal domain. Unlike general-purpose models, Ken1.0 was finetuned on a massive proprietary dataset containing over 30 million legal documents, including the Civil, Criminal, and Labor Codes of the Russian Federation, as well as extensive court practice records.

This model is designed to bridge the gap between generic AI and professional legal expertise.

Key Capabilities

• Deep Legal Understanding: Interprets complex Russian legal terminology and context
• Advisory: Drafts preliminary consultations on civil, criminal, and labor law
• Document Analysis: Can process and summarize legal texts
• Code Navigation: Provides references to specific articles and regulations

Technical Specifications

• Parameters: 67 billion
• Language: Russian
• Context Window: 32,768 tokens (~24,000 words)
• Precision: FP16
• Model Size: 135 GB
• Hardware Requirements:
  • GPU: A100 (80GB) or H100 recommended for inference
  • CPU: 200GB+ RAM for CPU inference
• Framework: PyTorch, Transformers

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

# Load model and tokenizer
model = AutoModelForCausalLM.from_pretrained(
    "KenanKoiushov/Ken1.0-67B",
    device_map="auto",
    torch_dtype="auto"
)
tokenizer = AutoTokenizer.from_pretrained("KenanKoiushov/Ken1.0-67B")

# Prepare messages
messages = [
    {"role": "system", "content": "Вы - юридический консультант по российскому праву."},
    {"role": "user", "content": "Какой срок исковой давности по гражданским делам?"}
]

# Generate response
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)

outputs = model.generate(
    **inputs,
    max_new_tokens=1024,
    temperature=0.7,
    top_p=0.9,
    do_sample=True
)

response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)

Training Details

• Base Architecture: Transformer-based decoder model
• Training Data: 30M+ Russian legal documents
  • Civil Code of the Russian Federation
  • Criminal Code of the Russian Federation
  • Labor Code of the Russian Federation
  • Court practice and case law
  • Legal commentary and analysis
• Specialization: Extensive training on Russian legal corpus

Performance Notes

• GPU Inference: ~2-5 seconds per response (A100 80GB)
• CPU Inference: 5-15 minutes per response (36+ cores recommended)
• Quantization: 4-bit/8-bit quantization supported for reduced memory footprint

Limitations

• This model is designed for informational and educational purposes only
• Not a substitute for professional legal advice
• May occasionally generate incorrect or outdated legal information
• Always consult qualified legal professionals for actual legal matters
• Trained primarily on Russian Federation law (as of training date)

License

This model is released for research and educational purposes. Commercial use requires separate licensing.

Disclaimer

Ken1.0-67B provides general legal information and should not be considered as professional legal advice. The model's outputs do not establish an attorney-client relationship. Users should always verify information with qualified legal professionals before making legal decisions.

Citation

If you use this model in your research, please cite:

@misc{ken1.0-67b,
  title={Ken1.0-67B: A Specialized Legal Language Model for Russian Law},
  author={Koiushov, Kenan},
  year={2025},
  publisher={HuggingFace},
  url={https://huggingface.co/KenanKoiushov/Ken1.0-67B}
}

Contact

For questions, feedback, or commercial licensing inquiries, please open an issue on the model repository.

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Model Version: 1.0
Release Date: December 2025
Status: Production Ready