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OpenOranje/TweeTaal-nl-en-0.6B

sourceHugging Faceapache-2.0updated 10mo agoView on Hugging Face
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OpenOranje/TweeTaal-nl-en-0.6B

Model Description

The TweeTaal-en-nl model has been fine-tuned on Dutch-English & English-Dutch translation pairs to provide accurate, fluent translations. The compact 0.6B parameter size makes it suitable for deployment in resource-constrained environments while maintaining strong translation quality.

Intended Use

Primary Use Case: Translating Dutch text to English / English text to Dutch across various domains

Recommended Applications:

  • —General-purpose Dutch-to-English and English-to-Dutch translation
  • —Content localization
  • —Cross-lingual communication tools
  • —Educational language learning applications

Performance

Benchmark Results

<img src="https://github.com/OpenOranje/content/raw/main/images/translation-benchmarks.png" alt="Benchmarks" width="800">

Training Details

Training Procedure

Method: Supervised Fine-Tuning (SFT)

  • —The model was trained on parallel Dutch-English text pairs
  • —Standard cross-entropy loss optimization
  • —The base Qwen3-0.6b model was adapted specifically for translation tasks

Training Data

The model was trained on Dutch-English parallel corpora. (Note: Specify your actual dataset details, such as:

  • —Dataset name and source
  • —Number of training examples
  • —Domain coverage (general, technical, literary, etc.)
  • —Data preprocessing steps)

Usage

Basic Usage Example

python
from transformers import AutoTokenizer, AutoModelForCausalLM

# Load model and tokenizer
model_name = "OpenOranje/TweeTaal-nl-en-0.6B"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Prepare input
dutch_text = "Hallo, hoe gaat het met je?"
prompt = f"Translate from Dutch to English:\n{dutch_text}"
message = [{"role":"user", "content": prompt}]
# Generate translation
inputs = tokenizer.apply_chat_template(message, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=128, temperature=0.7)
translation = tokenizer.decode(outputs[0], skip_special_tokens=True)

print(translation)

Prompt Format

The model expects input in the following format:

Translate the following text from Dutch to English:\n{dutch_text}
Translate the following text from English to Dutch:\n{english_text}

Inference Parameters

Recommended generation parameters:

  • —Temperature: 0.7 (adjust for creativity vs. consistency)
  • —Max tokens: Set based on expected translation length
  • —Top-p: 0.9 (nucleus sampling)

Limitations

  • —Context Length: Trained on 4096 Tokens
  • —Rare Words: May struggle with highly specialized terminology or rare vocabulary not well-represented in training data
  • —Informal Language: Performance on slang, dialects, or very informal Dutch may vary

Ethical Considerations

  • —Training Data Bias: The model may reflect biases present in the training data
  • —Cultural Nuances: Some cultural expressions may not translate perfectly

Contact

For questions or issues, please contact: [theaisarth@proton.me][kartikaggarwal98@gmail.com]

Additional Resources

Version History

  • —v1.0 (2025-10-24): Initial release

License: [Apache 2.0]