File size: 2,298 Bytes
e8ffa96 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 |
---
license: apache-2.0
language:
- en
library_name: transformers
tags:
- mortality
- actuary
- healthcare
- llama
- text-generation
datasets:
- world-mortality
widget:
- text: "What is the life expectancy in United States for 2024?"
---
# Morbid.AI v0.0.4 - 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
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("h3ir/morbid0.0.4")
model = AutoModelForCausalLM.from_pretrained("h3ir/morbid0.0.4")
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
```bash
curl https://api-inference.huggingface.co/models/h3ir/morbid0.0.4 \
-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
```bibtex
@misc{morbidai2024,
author = {h3ir},
title = {Morbid.AI: Mortality Prediction Model},
year = {2024},
publisher = {HuggingFace},
url = {https://huggingface.co/h3ir/morbid0.0.4}
}
```
## Contact
For questions: Visit [morbid.ai](https://morbid.ai) |