
# Myanmar-GPT

မြန်မာ(ဗမာ)လိုနားလည်သော GPT - Myanmar GPT 

Myanmar GPT is a model trained on a private Myanmar language dataset made by MinSiThu.
The project aims to make the Myanmar language available in the GPT2 Model.

Fine-tuning the MyanmarGPT model makes it easier to build a custom Myanmar language model than using alternative language models.

Reports on training the MyanmarGPT model are visualized at [MyanmarGPT Report](https://api.wandb.ai/links/minsithu/wn8yul90).

There is also 1.42 billion parameters MyanmarGPT-Big model with multilanguage support.
You are find [MyanmarGPT-Big Here](https://huggingface.co/jojo-ai-mst/MyanmarGPT-Big).

## How to use in your project

```
!pip install transformers
```

```python
from transformers import pipeline

generator = pipeline(model="jojo-ai-mst/MyanmarGPT")
outputs = generator("အီတလီ",do_sample=False)

print(outputs)
# [{'generated_text': 'အီတလီနိုင်ငံသည် ဥရောပတိုက်၏ တောင်ဘက်တွင် မြေထဲပင်လယ်ထဲသို့ ထိုးထွက်နေသော ကျွန်းဆွယ်ကြီးတစ်ခုဖြစ်၍ ပုံသဏ္ဌာန်အားဖြင့် မြင်းစီးဖိနပ်နှင့် တူလေသည်။ မြောက်ဘက်မှ တောင်ဘက်အငူစွန်းအထိ မိုင်ပေါင်း ၇၅ဝ ခန့် ရှည်လျား၍၊ ပျမ်းမျှမိုင် ၁ဝဝ မှ ၁၂ဝ ခန့်ကျယ်သည်။ အီတလီနိုင်ငံ၏ အကျယ်အဝန်းမှာ ဆာဒင်းနီးယားကျွန်း၊ စစ္စလီကျွန်းနှင့် အနီးပတ်ဝန်းကျင်ရှိ ကျွန်းကလေးများ အပါအဝင် ၁၁၆,၃၅၀ စတုရန်းမိုင်ရှိသည်။ '}]
```

### alternative ways

```python
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

model = GPT2LMHeadModel.from_pretrained("jojo-ai-mst/MyanmarGPT")
tokenizer = GPT2Tokenizer.from_pretrained("jojo-ai-mst/MyanmarGPT")

def generate_text(prompt, max_length=300, temperature=0.8, top_k=50):
    input_ids = tokenizer.encode(prompt, return_tensors="pt").cuda() # remove .cude() if only cpu
    output = model.generate(
        input_ids,
        max_length=max_length,
        temperature=temperature,
        top_k=top_k,
        pad_token_id=tokenizer.eos_token_id,
        do_sample=True
    )
    for result in output:
      generated_text = tokenizer.decode(result, skip_special_tokens=True)
      print(generated_text)

generate_text("အီတလီ ")
```


## Here are the guidelines for using the MyanmarGPT license,
- MyanmarGPT is free to use for everyone,
  
- **Must Do**
  - any project derived/finetuned from MyanmarGPT, used MyanmarGPT internally,
  - or modified MyanmarGPT, related to MyanmarGPT **must mention the citation below** in the corresponding project's page.
- the citation
```latex
@software{MyanmarGPT,
  author = {{MinSiThu}},
  title = {MyanmarGPT},
  version={1.1-SweptWood}
  url = {https://huggingface.co/jojo-ai-mst/MyanmarGPT},
  urldate = {2023-12-14}
  date = {2023-12-14},
}
```

For contact, reach me via [https://www.linkedin.com/in/min-si-thu/](https://www.linkedin.com/in/min-si-thu/)
{"language": ["my"], "license": "creativeml-openrail-m", "tags": ["Myanmar", "Burmese", "GPT2", "MyanmarGPT", "Nautral Language Processing"], "widget": [{"text": "\u1021\u102e\u1010\u101c\u102e", "example_title": "Example 1"}, {"text": "\u1021\u1014\u102f\u1015\u100a\u102c", "example_title": "Example 2"}, {"text": "\u1010\u101b\u102f\u1010\u103a", "example_title": "Example 3"}, {"text": "\u1000\u103b\u1031\u102c\u1000\u103a\u1001\u1031\u1010\u103a", "example_title": "Example 4"}, {"text": "\u1019\u103c\u1014\u103a\u1019\u102c\u1014\u102d\u102f\u1004\u103a\u1004\u1036", "example_title": "Example 5"}]}
transformers tensorboard safetensors gpt2 text-generation Myanmar Burmese GPT2 MyanmarGPT Nautral Language Processing my license:creativeml-openrail-m autotrain_compatible endpoints_compatible has_space text-generation-inference region:us