---
license: mit
language:
- en
base_model:
- google/flan-t5-base
---
# QuanTarot Model

## Overview
QuanTarot is a fine-tuned model designed to provide detailed and interactive tarot card readings. It leverages the `google/flan-t5-base` model and has been fine-tuned with custom tarot-related prompts and responses. The model supports interpreting card spreads, combining numerology insights, and providing meaningful guidance.

---

## Features
- **Tarot Card Readings**: Supports Rider-Waite deck interpretations for various spreads like Celtic Cross, Three-Card, and Six-Pointed Star.
- **Numerology Integration**: Offers insights by connecting numbers to tarot cards.
- **Interactive Responses**: Generates elegant, classical responses with a mysterious and insightful tone.

---

## Usage
### Python Example
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

# Load the model and tokenizer
model_name = "your-username/quantarot-model"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

# Example prompt
prompt = "What does The Fool card represent in my current situation?"
inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True)
outputs = model.generate(inputs["input_ids"], max_new_tokens=150)

# Decode and print the result
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)