Morbid.AI v0.0.1 - Mortality Prediction Model

Model Description

Morbid.AI is a specialized language model fine-tuned for mortality analysis and actuarial predictions. Based on Llama-2-7b, it's trained on the World Mortality Dataset to provide insights on:

Life expectancy calculations
Mortality trends analysis
Death probability estimations
Actuarial assessments
Country-specific mortality comparisons

Intended Use

This model is designed for:

Actuarial analysis
Healthcare research
Mortality trend analysis
Educational purposes

Note: This model should NOT be used for personal medical advice or life insurance underwriting decisions.

Training Data

Fine-tuned on:

World Mortality Dataset (2015-2024)
34,537 training examples
Countries: 200+ nations
Mortality metrics from official statistics

Usage

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("h3ir/morbid0.0.1")
model = AutoModelForCausalLM.from_pretrained("h3ir/morbid0.0.1")

prompt = "What are the mortality trends for Japan in 2023?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=200)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)

API Usage

curl https://api-inference.huggingface.co/models/h3ir/morbid0.0.1 \
  -X POST \
  -d '{"inputs": "What is the life expectancy in France?"}' \
  -H "Authorization: Bearer YOUR_TOKEN"

Model Performance

Training Loss: 0.42
Validation Accuracy: 87%
Specialization: Mortality & Actuarial Data

Limitations

Data limited to 2015-2024
Predictions are statistical estimates
Should not replace professional actuarial advice
May have biases from source data

Citation

@misc{morbidai2024,
  author = {h3ir},
  title = {Morbid.AI: Mortality Prediction Model},
  year = {2024},
  publisher = {HuggingFace},
  url = {https://huggingface.co/h3ir/morbid0.0.1}
}

Contact

For questions: Visit morbid.ai

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