Update README.md

README.md

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----
-license: cc-by-4.0
----
+---
+license: cc-by-4.0
+
+datasets:
+  - matbahasa/TALPCo
+
+language:
+  - my
+  - en
+  - ja
+
+base_model:
+  - google/mt5-small
+
+tags:
+  - translation
+  - seq2seq
+  - fine-tuned
+  - text-to-text
+
+training_info:
+  optimizer: AdamW
+  epochs: 5
+  batch_size: 4
+  learning_rate: 1e-5
+  max_length: 256
+---
+
+#ShweYi-17K-mt5-small
+
+Fine-tuned [`google/mt5-small`](https://huggingface.co/google/mt5-small) model for multilingual translation between **English**, **Myanmar (Burmese)**, and **Japanese**, using the [TALPCo dataset](https://github.com/matbahasa/TALPCo) (CC BY 4.0).
+
+##Training Info
+
+- Optimizer: AdamW  
+- Epochs: 5  
+- Batch Size: 4  
+- Learning Rate: 1e-5  
+- Max Length: 256  
+
+##How to Use
+
+```python
+from transformers import AutoTokenizer, MT5ForConditionalGeneration
+import torch
+
+MAX_LENGTH = 256
+
+tokenizer = AutoTokenizer.from_pretrained("flexavior/ShweYi-17K-mt5-small", legacy=True)
+model = MT5ForConditionalGeneration.from_pretrained("flexavior/ShweYi-17K-mt5-small")
+
+if torch.cuda.is_available():
+    model = model.to("cuda")
+
+print("Multilingual MT5 Translator is ready!")
+print("Format: translate myn to jpn: အခု ဘယ်အချိန် ရှိပြီလဲ.")
+print("Type 'exit' to quit.\n")
+
+while True:
+    user_input = input(">>> ")
+    if user_input.strip().lower() == "exit":
+        break
+
+    input_ids = tokenizer(
+        user_input,
+        return_tensors="pt",
+        max_length=MAX_LENGTH,
+        padding="max_length",
+        truncation=True
+    ).input_ids
+
+    if torch.cuda.is_available():
+        input_ids = input_ids.to("cuda")
+
+    with torch.no_grad():
+        output_ids = model.generate(
+            input_ids=input_ids,
+            max_length=MAX_LENGTH,
+            num_beams=4,
+            early_stopping=True
+        )
+
+    output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+    print(f" Translation: {output_text}\n")
+
+#Citations
+If you use ShweYi-17K-mt5-small in your research, cite:
+
+@misc{flexavior2025shweyi17kmultilingual,
+  author       = {Flexavior},
+  title        = {Flexavior: shweyi-17k-multilingual-en-my-ja},
+  year         = {2025},
+  url          = {https://huggingface.co/flexavior/ShweYi-17K-mt5-small},
+  note         = {Fine-tuned mT5 for English, Myanmar, and Japanese translation. Dataset: TALPCO.}
+}
+
+And the dataset source:
+
+@article{published_papers/22434604,
+  title = {TUFS Asian Language Parallel Corpus (TALPCo)},
+  author = {Hiroki Nomoto and Kenji Okano and David Moeljadi and Hideo Sawada},
+  journal = {言語処理学会 第24回年次大会 発表論文集},
+  pages = {436--439},
+  year = {2018}
+}
+