ShweYon-v1.2-Base is a specialized language model based on the Qwen2.5-1.5B architecture, meticulously optimized for the Myanmar (Burmese) language. This version features a significant Vocabulary Expansion designed to solve common tokenization inefficiencies in Burmese NLP.

📊 Technical Specifications

Feature	Specification
Base Architecture	Qwen2.5-1.5B
New Vocab Size	152,858
Added Tokens	1,418 (Cumulative)
Model Size Increase	~4.73 MB (+0.40% total weight)
Training Type	Continual Pre-training (CPT)
Language	Myanmar (Burmese)

💻 Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "URajinda/ShweYon-Qwen2.5-Burmese-1.5B-v1.2" 

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

text = "မြန်မာနိုင်ငံသည်"
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))