monk-gpt

Monk GPT - Philosophical Wisdom Assistant

Model Description

Monk GPT is a fine-tuned GPT-2 model trained on philosophical conversations about life, death, relationships, career, education, and personal growth. The model responds as a wise monk, offering thoughtful, compassionate, and reflective answers to user questions.

• Developed by: Utpalendu Barman
• Model type: Causal Language Model (GPT-2)
• Language: English
• Base model: GPT-2
• License: MIT

Intended Uses

Direct Use:
This model is designed for philosophical Q&A and reflective conversation. It can be used for:

• Personal reflection and journaling
• Educational purposes
• Conversational AI applications
• Meditation and mindfulness tools

Out-of-Scope Use:
The model is not intended for:

• Medical, legal, or professional advice
• Factual information retrieval
• Harmful or manipulative content

Bias, Risks, and Limitations

• The model reflects the biases present in its training data and base GPT-2 model
• Responses are philosophical and reflective, not factual
• May generate unpredictable or inappropriate content
• Should be used with human oversight

How to Get Started

from transformers import GPT2Tokenizer, GPT2LMHeadModel

model_name = "utpalendu/monk-gpt"
tokenizer = GPT2Tokenizer.from_pretrained(model_name)
model = GPT2LMHeadModel.from_pretrained(model_name)

def ask_monk(question):
    prompt = f"Q: {question} A:"
    inputs = tokenizer.encode(prompt, return_tensors="pt")
    outputs = model.generate(
        inputs,
        max_length=200,
        temperature=0.8,
        do_sample=True,
        pad_token_id=tokenizer.eos_token_id
    )
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return response.split("A:")[-1].strip()

print(ask_monk("What is the meaning of life?"))