Ramana Maharshi Teaching Assistant — Phi-3 Mini LoRA
A LoRA fine-tuned version of Phi-3-mini-4k-instruct trained on verified teachings of Sri Ramana Maharshi.
Training
- Base model:
microsoft/Phi-3-mini-4k-instruct - Method: QLoRA (4-bit NF4) + SFT → DPO
- SFT data: Single-turn and multi-turn Q&A grounded in canonical texts
- DPO data: Preference pairs (verified teachings vs. generic responses)
- Canonical sources: Who Am I?, Talks with Sri Ramana Maharshi, Ulladu Narpadu
- LoRA rank: 16 | Alpha: 32 | Target: all attention + MLP projection layers
Usage
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "SriRamanaAtmic/AtmicIntelv1"
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype = torch.bfloat16,
device_map = "auto",
trust_remote_code = True,
)
SYSTEM = (
"You are a knowledgeable and compassionate guide to the teachings of "
"Sri Ramana Maharshi. Answer questions about Self-enquiry, the nature "
"of the Self, surrender, and the path to liberation, grounded in his "
"actual teachings."
)
messages = [
{"role": "system", "content": SYSTEM},
{"role": "user", "content": "What is self-enquiry?"},
]
text = tokenizer.apply_chat_template(messages, tokenize=False,
add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
with torch.no_grad():
out = model.generate(
**inputs,
max_new_tokens = 512,
temperature = 0.7,
top_p = 0.9,
repetition_penalty = 1.1,
do_sample = True,
)
print(tokenizer.decode(out[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))
About Sri Ramana Maharshi
Sri Ramana Maharshi (1879–1950) was one of the greatest sages of modern India. His principal teaching was Atma Vichara (Self-enquiry): the direct path of tracing the sense of "I" back to its source, the Self — pure, undivided awareness. He is revered across traditions for the simplicity, depth, and transformative power of his teachings.