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Model Description

LLaMAX is a language model with powerful multilingual capabilities without loss instruction-following capabilities.

We collected extensive training sets in 102 languages for continued pre-training of Llama2 and leveraged the English instruction fine-tuning dataset, Alpaca, to fine-tune its instruction-following capabilities.

๐Ÿ”ฅ Effortless Multilingual Translation with a Simple Prompt

LLaMAX supports translation between more than 100 languages, surpassing the performance of similarly scaled LLMs.

def Prompt_template(query, src_language, trg_language):
    instruction = f'Translate the following sentences from {src_language} to {trg_language}.'
    prompt = (
        'Below is an instruction that describes a task, paired with an input that provides further context. '
        'Write a response that appropriately completes the request.\n'
        f'### Instruction:\n{instruction}\n'
        f'### Input:\n{query}\n### Response:'
    )
    return prompt

And then run the following codes to execute translation:

from transformers import AutoTokenizer, LlamaForCausalLM

model = LlamaForCausalLM.from_pretrained(PATH_TO_CONVERTED_WEIGHTS)
tokenizer = AutoTokenizer.from_pretrained(PATH_TO_CONVERTED_TOKENIZER)

query = "ไฝ ๅฅฝ๏ผŒไปŠๅคฉๆ˜ฏไธชๅฅฝๆ—ฅๅญ"
prompt = Prompt_template(query, 'Chinese', 'English')
inputs = tokenizer(prompt, return_tensors="pt")

generate_ids = model.generate(inputs.input_ids, max_length=30)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# => "Hello, today is a good day"

๐Ÿ”ฅ Excellent Translation Performance

LLaMAX3-8B-Alpaca achieves an average spBLEU score improvement of over 5 points compared to the LLaMA3-8B-Alpaca model on the Flores-101 dataset.

System Size en-X (COMET) en-X (BLEU) zh-X (COMET) zh-X (BLEU) de-X (COMET) de-X (BLEU) ne-X (COMET) ne-X (BLEU) ar-X (COMET) ar-X (BLEU) az-X (COMET) az-X (BLEU) ceb-X (COMET) ceb-X (BLEU)
LLaMA3-8B-Alpaca 8B 67.97 17.23 64.65 10.14 64.67 13.62 62.95 7.96 63.45 11.27 60.61 6.98 55.26 8.52
LLaMAX3-8B-Alpaca 8B 75.52 22.77 73.16 14.43 73.47 18.95 75.13 15.32 72.29 16.42 72.06 12.41 68.88 15.85
System Size X-en (COMET) X-en (BLEU) X-zh (COMET) X-zh (BLEU) X-de (COMET) X-de (BLEU) X-ne (COMET) X-ne (BLEU) X-ar (COMET) X-ar (BLEU) X-az (COMET) X-az (BLEU) X-ceb (COMET) X-ceb (BLEU)
LLaMA3-8B-Alpaca 8B 77.43 26.55 73.56 13.17 71.59 16.82 46.56 3.83 66.49 10.20 58.30 4.81 52.68 4.18
LLaMAX3-8B-Alpaca 8B 81.28 31.85 78.34 16.46 76.23 20.64 65.83 14.16 75.84 15.45 70.61 9.32 63.35 12.66

Supported Languages

Akrikaans (af), Amharic (am), Arabic (ar), Armenian (hy), Assamese (as), Asturian (ast), Azerbaijani (az), Belarusian (be), Bengali (bn), Bosnian (bs), Bulgarian (bg), Burmese (my), Catalan (ca), Cebuano (ceb), Chinese Simpl (zho), Chinese Trad (zho), Croatian (hr), Czech (cs), Danish (da), Dutch (nl), English (en), Estonian (et), Filipino (tl), Finnish (fi), French (fr), Fulah (ff), Galician (gl), Ganda (lg), Georgian (ka), German (de), Greek (el), Gujarati (gu), Hausa (ha), Hebrew (he), Hindi (hi), Hungarian (hu), Icelandic (is), Igbo (ig), Indonesian (id), Irish (ga), Italian (it), Japanese (ja), Javanese (jv), Kabuverdianu (kea), Kamba (kam), Kannada (kn), Kazakh (kk), Khmer (km), Korean (ko), Kyrgyz (ky), Lao (lo), Latvian (lv), Lingala (ln), Lithuanian (lt), Luo (luo), Luxembourgish (lb), Macedonian (mk), Malay (ms), Malayalam (ml), Maltese (mt), Maori (mi), Marathi (mr), Mongolian (mn), Nepali (ne), Northern Sotho (ns), Norwegian (no), Nyanja (ny), Occitan (oc), Oriya (or), Oromo (om), Pashto (ps), Persian (fa), Polish (pl), Portuguese (pt), Punjabi (pa), Romanian (ro), Russian (ru), Serbian (sr), Shona (sn), Sindhi (sd), Slovak (sk), Slovenian (sl), Somali (so), Sorani Kurdish (ku), Spanish (es), Swahili (sw), Swedish (sv), Tajik (tg), Tamil (ta), Telugu (te), Thai (th), Turkish (tr), Ukrainian (uk), Umbundu (umb), Urdu (ur), Uzbek (uz), Vietnamese (vi), Welsh (cy), Wolof (wo), Xhosa (xh), Yoruba (yo), Zulu (zu)

Model Index

We implement multiple versions of the LLaMAX model, the model links are as follows:

Model LLaMAX LLaMAX-Alpaca
Llama-2 Link Link
Llama-3 Link Link

Citation

If our model helps your work, please cite this paper:

@article{lu2024llamax,
  title={LLaMAX: Scaling Linguistic Horizons of LLM by Enhancing Translation Capabilities Beyond 100 Languages},
  author={Lu, Yinquan and Zhu, Wenhao and Li, Lei and Qiao, Yu and Yuan, Fei},
  journal={arXiv preprint arXiv:2407.05975},
  year={2024}
}
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