from transformers import pipeline
generator = pipeline(
"text-generation",
model="11-47/SmolLM-135M-Tarot-Zodiac-Reasoning",
device="cuda"
)
question = "What does The Tower card mean for someone with a Scorpio rising going through a major life transition?"
output = generator(
[{"role": "user", "content": question}],
max_new_tokens=256,
return_full_text=False
)[0]
print(output["generated_text"])
Intended Uses
• Tarot Readings: Generate insightful interpretations of cards and spreads (single card, 3-card, Celtic Cross, etc.).
• Zodiac & Astrology: Personalized horoscopes, compatibility analysis, and planetary transits.
• Mystical Reasoning: Symbolic interpretation, dream analysis, spiritual advice with logical structure.
• Lightweight Deployment: Runs great on phones, laptops, or embedded devices.
• Fun / Educational spiritual chatbots.
Limitations
• Very small model (135M) → Can be less coherent on complex multi-card spreads or highly nuanced queries compared to larger models.
• Knowledge is synthetic / training-data driven — treat outputs as inspirational rather than definitive divination.
• May occasionally hallucinate card meanings or astrological facts.
• Not a replacement for professional tarot/astrology consultation.
Training Procedure
• Framework: Hugging Face TRL (Transformers Reinforcement Learning library)
• Method: SFT on assistant responses in chat format.
• Framework Versions:
◦ TRL: 1.8.0
◦ Transformers: 5.13.1
◦ PyTorch: 2.10.0+cu128
◦ Datasets: 5.0.0
Citation
@misc{smollm-tarot-zodiac-reasoning,
author = {11-47},
title = {SmolLM-135M-Tarot-Zodiac-Reasoning},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/11-47/SmolLM-135M-Tarot-Zodiac-Reasoning}
}
@software{vonwerra2020trl,
title = {{TRL: Transformers Reinforcement Learning}},
author = {von Werra, Leandro and others},
url = {https://github.com/huggingface/trl},
year = {2020}
}