99 lines
3.6 KiB
Markdown
99 lines
3.6 KiB
Markdown
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---
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base_model: HuggingFaceTB/SmolLM-135M-Instruct
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library_name: transformers
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model_name: SmolLM-135M-Tarot-Zodiac-Reasoning
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tags:
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- generated_from_trainer
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- sft
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- trl
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- conversational
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- text-generation
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- tarot
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- zodiac
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- astrology
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- reasoning
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datasets:
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- 11-47/The_Prophet_Tarot_Zodiac_50K
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- 11-47/The_Prophet_Tarot_Zodiac_5K
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- 11-47/The_Prophet_Tarot_Zodiac_5K_seed
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license: apache-2.0 # Assuming standard; update if needed
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language:
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- en
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---
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# SmolLM-135M-Tarot-Zodiac-Reasoning
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**By 11-47**
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A fine-tuned **135M parameter** model specialized in **Tarot interpretation, Zodiac insights, and mystical reasoning**. Built on top of [HuggingFaceTB/SmolLM-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct) using Supervised Fine-Tuning (SFT) with TRL.
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This tiny but mighty model blends modern LLM capabilities with esoteric knowledge—perfect for lightweight tarot readings, astrological guidance, symbolic reasoning, and creative spiritual conversations on edge devices or low-resource setups.
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## Model Details
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- **Base Model**: `HuggingFaceTB/SmolLM-135M-Instruct`
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- **Parameters**: 135M (super efficient!)
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- **Tensor Type**: F32 (Safetensors)
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- **Training Method**: SFT (Supervised Fine-Tuning) via TRL
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- **Datasets**:
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- `11-47/The_Prophet_Tarot_Zodiac_50K` (main dataset)
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- `11-47/The_Prophet_Tarot_Zodiac_5K`
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- `11-47/The_Prophet_Tarot_Zodiac_5K_seed` (seed / validation)
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The training focuses on conversational tarot spreads, zodiac interpretations, symbolic reasoning, and blending mystical traditions with logical explanations.
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## Quick Start
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```python
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from transformers import pipeline
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generator = pipeline(
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"text-generation",
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model="11-47/SmolLM-135M-Tarot-Zodiac-Reasoning",
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device="cuda" # or "cpu"
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)
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question = "What does The Tower card mean for someone with a Scorpio rising going through a major life transition?"
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output = generator(
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[{"role": "user", "content": question}],
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max_new_tokens=256,
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return_full_text=False
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)[0]
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print(output["generated_text"])
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Intended Uses
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• Tarot Readings: Generate insightful interpretations of cards and spreads (single card, 3-card, Celtic Cross, etc.).
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• Zodiac & Astrology: Personalized horoscopes, compatibility analysis, and planetary transits.
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• Mystical Reasoning: Symbolic interpretation, dream analysis, spiritual advice with logical structure.
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• Lightweight Deployment: Runs great on phones, laptops, or embedded devices.
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• Fun / Educational spiritual chatbots.
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Limitations
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• Very small model (135M) → Can be less coherent on complex multi-card spreads or highly nuanced queries compared to larger models.
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• Knowledge is synthetic / training-data driven — treat outputs as inspirational rather than definitive divination.
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• May occasionally hallucinate card meanings or astrological facts.
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• Not a replacement for professional tarot/astrology consultation.
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Training Procedure
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• Framework: Hugging Face TRL (Transformers Reinforcement Learning library)
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• Method: SFT on assistant responses in chat format.
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• Framework Versions:
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◦ TRL: 1.8.0
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◦ Transformers: 5.13.1
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◦ PyTorch: 2.10.0+cu128
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◦ Datasets: 5.0.0
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Citation
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@misc{smollm-tarot-zodiac-reasoning,
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author = {11-47},
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title = {SmolLM-135M-Tarot-Zodiac-Reasoning},
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year = {2026},
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publisher = {Hugging Face},
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url = {https://huggingface.co/11-47/SmolLM-135M-Tarot-Zodiac-Reasoning}
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}
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# Cite TRL
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@software{vonwerra2020trl,
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title = {{TRL: Transformers Reinforcement Learning}},
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author = {von Werra, Leandro and others},
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url = {https://github.com/huggingface/trl},
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year = {2020}
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}
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