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Model: LLaMAX/LLaMAX3-8B Source: Original Platform
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README.md
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---
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tags:
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- Multilingual
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license: mit
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language:
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- af
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- am
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- ar
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- hy
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- as
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- ast
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- az
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- bn
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- my
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- ceb
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- zho
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- hr
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- cs
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- da
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- nl
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- en
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- et
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- ja
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- jv
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- kea
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- kam
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- kn
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- kk
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- km
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- ko
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- ky
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- lo
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- ln
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- luo
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- uk
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- umb
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- ur
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- uz
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- vi
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- cy
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- wo
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- xh
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- yo
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- zu
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---
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### Model Sources
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- **Paper**: LLaMAX: Scaling Linguistic Horizons of LLM by Enhancing Translation Capabilities Beyond 100 Languages
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- **Link**: https://arxiv.org/pdf/2407.05975
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- **Repository**: https://github.com/CONE-MT/LLaMAX/
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- **Demo**: https://huggingface.co/spaces/vilarin/LLaMAX3-Translator Thanks for the efforts from @AnnioDance.
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### Model Description
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LLaMAX3-8B is a multilingual language base model, developed through continued pre-training on Llama3, and supports over 100 languages.
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LLaMAX3-8B can serve as a base model to support downstream multilingual tasks but without instruct-following capability.
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We further fine-tune LLaMAX3-8B on Alpaca dataset to enhance its instruct-following capabilities. The model is available at https://huggingface.co/LLaMAX/LLaMAX3-8B-Alpaca.
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### Supported Languages
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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)
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### Model Index
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| Model | LLaMAX | LLaMAX-Alpaca |
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|---------|----------------------------------------------------------|-----------------------------------------------------------------|
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| Llama-2 | [Link](https://huggingface.co/LLaMAX/LLaMAX2-7B) | [Link](https://huggingface.co/LLaMAX/LLaMAX2-7B-Alpaca) |
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| Llama-3 | [Link](https://huggingface.co/LLaMAX/LLaMAX3-8B) | [Link](https://huggingface.co/LLaMAX/LLaMAX3-8B-Alpaca) |
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### Citation
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If our model helps your work, please cite this paper:
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```
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@inproceedings{lu-etal-2024-llamax,
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title = "{LL}a{MAX}: Scaling Linguistic Horizons of {LLM} by Enhancing Translation Capabilities Beyond 100 Languages",
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author = "Lu, Yinquan and
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Zhu, Wenhao and
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Li, Lei and
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Qiao, Yu and
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Yuan, Fei",
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editor = "Al-Onaizan, Yaser and
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Bansal, Mohit and
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Chen, Yun-Nung",
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booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",
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month = nov,
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year = "2024",
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address = "Miami, Florida, USA",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2024.findings-emnlp.631",
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doi = "10.18653/v1/2024.findings-emnlp.631",
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pages = "10748--10772",
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abstract = "Large Language Models (LLMs) demonstrate remarkable translation capabilities in high-resource language tasks, yet their performance in low-resource languages is hindered by insufficient multilingual data during pre-training. To address this, we conduct extensive multilingual continual pre-training on the LLaMA series models, enabling translation support across more than 100 languages. Through a comprehensive analysis of training strategies, such as vocabulary expansion and data augmentation, we develop LLaMAX. Remarkably, without sacrificing its generalization ability, LLaMAX achieves significantly higher translation performance compared to existing open-source LLMs (by more than 10 spBLEU points) and performs on-par with specialized translation model (M2M-100-12B) on the Flores-101 benchmark. Extensive experiments indicate that LLaMAX can serve as a robust multilingual foundation model. The code and the models are publicly available.",
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}
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```
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config.json
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"vocab_size": 128256
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}
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"model.layers.5.self_attn.k_proj.weight": "model-00002-of-00007.safetensors",
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"model.layers.5.self_attn.o_proj.weight": "model-00002-of-00007.safetensors",
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"model.layers.6.input_layernorm.weight": "model-00002-of-00007.safetensors",
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"model.layers.6.mlp.down_proj.weight": "model-00002-of-00007.safetensors",
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"model.layers.6.mlp.gate_proj.weight": "model-00002-of-00007.safetensors",
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|
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|
||||
"model.norm.weight": "model-00007-of-00007.safetensors"
|
||||
}
|
||||
}
|
||||
4
special_tokens_map.json
Normal file
4
special_tokens_map.json
Normal file
@@ -0,0 +1,4 @@
|
||||
{
|
||||
"bos_token": "<|begin_of_text|>",
|
||||
"eos_token": "<|end_of_text|>"
|
||||
}
|
||||
410504
tokenizer.json
Normal file
410504
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
2062
tokenizer_config.json
Normal file
2062
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user