metadata
license: mit
language:
- my
pipeline_tag: text-generation
The Simbolo's Myanmar SAR GPT symbol is trained on a dataset of 1 million Burmese data and pre-trained using the GPT-2 architecture. Its purpose is to serve as a foundational pre-trained model for the Burmese language, facilitating fine-tuning for specific applications of different tasks such as creative writing, chatbot, machine translation etc.
How to use
!pip install transformers
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Simbolo-Servicio/myanmar-sar-gpt")
model = AutoModelForCausalLM.from_pretrained("Simbolo-Servicio/myanmar-sar-gpt")
input_text = ""
input_ids = tokenizer.encode(input_text, return_tensors='pt')
output = model.generate(input_ids, max_length=100)
print(tokenizer.decode(output[0], skip_special_tokens=True))
### Limitations and bias