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---
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
```python
!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
We have yet to thoroughly investigate the potential bias inherent in this model. Regarding transparency, it's important to note that the model is primarily trained on data from the Unicode Burmese(Myanmar) language.
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