Parameter	Value
Base model	Qwen/Qwen2.5-0.5B-Instruct (500M params)
Method	QLoRA (LoRA r=16, alpha=32, NF4 4-bit)
Trainable params	1,081,344 / 495M (0.22%)
Epochs	3
GPU	NVIDIA RTX 3050 Laptop
Training time	48 seconds
Final train loss	3.027
Token accuracy	49.4%

Usage

python

from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel

base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct")
tokenizer = AutoTokenizer.from_pretrained("ProfRutPatel/geopolitics-india-qwen2.5-0.5b-lora")
model = PeftModel.from_pretrained(base, "ProfRutPatel/geopolitics-india-qwen2.5-0.5b-lora")

messages = [{"role": "user", "content": "What are India's key geopolitical challenges?"}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors='pt')
out = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(out[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))

Sample Output

India faces strategic dependencies in the Indian Ocean, regional security tensions, cybersecurity threats, growing Middle East influence disputes, resource management challenges, and serious climate change impacts on its economy and infrastructure.