Typhoon 2.1 Gemma 3 KordTranslate EN-TH 4B is a bilingual English ↔ Thai translation model fine-tuned from typhoon-ai/typhoon2.1-gemma3-4b for high-quality machine translation between Thai and English.

The model is instruction-tuned specifically for translation tasks using bilingual translation datasets while preserving the strong language understanding inherited from the Typhoon base model.

✨ Features

🇺🇸 English → Thai translation
🇹🇭 Thai → English translation
Instruction-tuned for translation
Built on Typhoon2.1 Gemma 3 4B
Lightweight and suitable for local inference

Item	Value
Model	`KordAI/Typhoon-Gemma3-KordTranslate-EN-TH-4B`
Base Model	`typhoon-ai/typhoon2.1-gemma3-4b`
Architecture	Gemma 3 (4B)
Task	Machine Translation
Languages	English, Thai
Fine-tuning	Supervised Fine-Tuning (SFT)

This model is optimized for:

English → Thai translation
Thai → English translation
Localization
Educational applications
Chatbot translation
API integration
Batch document translation

For the best performance, use the prompt templates below.

📝 Prompt Templates

For optimal translation quality, structure your inputs exactly as shown below depending on the translation direction.

English → Thai

text

Translate the following English text to Thai.

### English:
[Your English text here]

Thai → English

text

Translate the following Thai text to English.


### Thai:
[Your Thai text here]

🐍 Inference Code (Python / Transformers)

python

from transformers import AutoModelForCausalLM, AutoTokenizer


# Hugging Face repository
model_name = "KordAI/Typhoon-Gemma3-KordTranslate-EN-TH-4B"


# Load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained(model_name)

model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype="auto",
    device_map="auto"
)

prompt = """
Translate the following English text to Thai.


### English:
But friends, I am so gay, that if I had a wife, I would encourage her to cheat on me.
"""

messages = [
    {"role": "user", "content": prompt}

]

text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True


)

model_inputs = tokenizer([text], return_tensors="pt").to(model.device)

generated_ids = model.generate(
    **model_inputs,
    max_new_tokens=512
)

output_ids = generated_ids[0][len(model_inputs.input_ids[0]):]

translation = tokenizer.decode(
    output_ids,
    skip_special_tokens=True
).strip()


print(translation)

🏋️ Training

This model is fine-tuned from typhoon-ai/typhoon2.1-gemma3-4b using supervised instruction tuning on bilingual English–Thai translation datasets.

The model is trained to perform direct translation between:

🇺🇸 English → Thai
🇹🇭 Thai → English

while maintaining natural, fluent, and context-aware outputs.

⚠️ Limitations

Translation quality may decrease on highly specialized domains such as medical, legal, or scientific texts.
Proper nouns and newly coined terminology may require manual verification.
The model may occasionally hallucinate or paraphrase ambiguous inputs.
Human review is recommended for production-critical translations.

Special thanks to:

Typhoon AI for the excellent typhoon2.1-gemma3-4b base model.
KordAI for developing and fine-tuning the translation model.
Unsloth for enabling efficient supervised fine-tuning.
llama.cpp for the GGUF format and inference ecosystem.
The open-source AI community for advancing multilingual language models.

📖 Citation

bibtex

@misc{kordtranslate2026,
  title={Typhoon Gemma3 KordTranslate EN-TH 4B},
  author={KordAI},
  year={2026},
  publisher={Hugging Face},
  howpublished={https://huggingface.co/KordAI/Typhoon-Gemma3-KordTranslate-EN-TH-4B}
}