AtmaLLaMA

Model Details

Model Name: AtmaLLaMA
Model Type: Fine-tuned LLaMA 2
Domain: Philosophy, Spirituality, Ancient Wisdom
Training Data: Bhagavad Gita, Patanjali Yoga Sutras, and other philosophical texts
Hosting Platform: Hugging Face
License: MIT

Model Description

AtmaLLaMA is a fine-tuned version of LLaMA 2, trained on ancient philosophical texts such as the Bhagavad Gita and the Patanjali Yoga Sutras. It is designed to generate insightful, spiritually aligned responses based on Indian philosophical wisdom. The model aims to provide thoughtful and meaningful discourse on topics related to self-awareness, dharma, meditation, and ethical living.

Use Cases

• Answering philosophical and spiritual queries
• Generating summaries and interpretations of ancient texts
• Assisting in guided meditation and self-reflection exercises
• Exploring ethical and moral dilemmas based on Indian philosophy

Model Performance

• Accuracy: The model generates highly relevant responses in the domain of Indian philosophy and spirituality. However, it may not be perfect in complex theological debates or contemporary issues outside its training domain.
• Biases & Limitations: The model primarily reflects the perspectives of the texts it was trained on. While it provides coherent answers, users should cross-reference responses with authentic sources for deeper study.
• Handling Misinformation: The model is not designed to be a substitute for scholarly research and should be used for guidance rather than absolute truths.

Ethical Considerations

• The model should not be used for religious debates or as an authoritative source of religious doctrine.
• Users should verify responses for accuracy when using the model in academic or professional settings.
• The model does not replace spiritual guidance from qualified practitioners.

How to Use

Using model and tokenizer directly

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "RakshitAi/AtmaLLaMA"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

input_text = "What is the essence of dharma?"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)

or using pipeline

from transformers import pipeline

model_name = "RakshitAi/AtmaLLaMA"
generator = pipeline("text-generation", model=model_name)

input_text = "What is the essence of dharma?"
response = generator(input_text, max_length=200, do_sample=True)
print(response[0]["generated_text"])

Future Improvements

• Expanding training data to include Upanishads, Vedas, and other spiritual texts
• Improving response coherence and contextual understanding
• Fine-tuning on contemporary philosophical discussions for broader relevance

Acknowledgments

Special thanks to the authors and translators of the Bhagavad Gita and Patanjali Yoga Sutras for their invaluable contributions to spiritual wisdom.