Hala-700M

Hala: Arabic‑Centric Instruction & Translation Models

<p align="center"> <img src="https://i.ibb.co/pvhp1XfJ/halalogo.png" alt="Hala logo" width="550" /> </p>

Paper: Hala Technical Report: Building Arabic‑Centric Instruction & Translation Models at Scale

Authors: Hasan Abed Al Kader Hammoud*, Mohammad Zbeeb*, Bernard Ghanem

Affiliation: King Abdullah University of Science and Technology (KAUST)

*Equal contribution

In Arabic, حلا (Hala) conveys sweetness and beauty—qualities long associated with the language itself. In this spirit, we call our models Hala.

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🔗 Quick Links

• Models & Data (Hugging Face collection): https://huggingface.co/collections/hammh0a/hala-68bf02b34a14b9f22305ab3a
• Contact: [email protected]

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Example

from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline

model_id = "hammh0a/Hala-700M"  # pick a released Hala model

tok = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id, torch_dtype="auto", device_map="auto"
)

# Use chat template
messages = [
    {"role": "system", "content": "أنت مساعد خبير في الفيزياء."},
    {"role": "user", "content": "اشرح بإيجاز مبدأ الانحفاظ في الفيزياء، وأعطني مثالاً يومياً."},
]

prompt = tok.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)

pipe = pipeline("text-generation", model=model, tokenizer=tok)
out = pipe(prompt, max_new_tokens=256, do_sample=False)

print(out[0]["generated_text"])

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📊 Results

Hala models are placed at the end of each size category; best Average per category is in bold.

≤2B parameters

7B–9B parameters

Evaluation protocol: lighteval on ArabicMMLU (OALL‑2) excluding AlRage.

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📚 Citation

If you find Hala useful, please cite:

@misc{hammoud2025halatechnicalreportbuilding,
      title={Hala Technical Report: Building Arabic-Centric Instruction & Translation Models at Scale}, 
      author={Hasan Abed Al Kader Hammoud and Mohammad Zbeeb and Bernard Ghanem},
      year={2025},
      url={https://arxiv.org/abs/2509.14008}, 
}