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README.md
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Original ALMA Model [ALMA-7B](https://huggingface.co/haoranxu/ALMA-7B). (26.95GB)
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ALMA-7B-Ja is a machine translation model that uses ALMA's learning method to translate Japanese to English.(13.3GB)
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Like the original model, This model has been verified that it also has a translation
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german and english
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Chinese and English
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Icelandic and English
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Czech and English
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Models | de | cs | is | zh | ru/jp | Avg. |
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[webbigdata/ALMA-7B-Ja-GPTQ-Ja-En](https://huggingface.co/webbigdata/ALMA-7B-Ja-GPTQ-Ja-En)
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**ALMA** (**A**dvanced **L**anguage **M**odel-based tr**A**nslator) is an LLM-based translation model, which adopts a new translation model paradigm: it begins with fine-tuning on monolingual data and is further optimized using high-quality parallel data. This two-step fine-tuning process ensures strong translation performance.
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Please find more details in their [paper](https://arxiv.org/abs/2309.11674).
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```
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Original ALMA Model [ALMA-7B](https://huggingface.co/haoranxu/ALMA-7B). (26.95GB)
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ALMA-7B-Ja is a machine translation model that uses ALMA's learning method to translate Japanese to English.(13.3GB)
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The original ALMA-7B supports English and Russian(ru) translation. This model supports Japanese(ja) and English translations instead of Russian.
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Like the original model, This model has been verified that it also has a translation ability between the following languages, but if you want the translation function for these languages, it is better to use the original [ALMA-13B model](https://huggingface.co/haoranxu/ALMA-13B).
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German(de) and English(en)
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Chinese(zh) and English(en)
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Icelandic(is) and English(en)
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Czech(cs) and English(en)
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Models | de | cs | is | zh | ru/jp | Avg. |
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|----------------|--------|--------|--------|--------|--------|--------|
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[webbigdata/ALMA-7B-Ja-GPTQ-Ja-En](https://huggingface.co/webbigdata/ALMA-7B-Ja-GPTQ-Ja-En)
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**ALMA** (**A**dvanced **L**anguage **M**odel-based tr**A**nslator) is an LLM-based translation model, which adopts a new translation model paradigm: it begins with fine-tuning on monolingual data and is further optimized using high-quality parallel data. This two-step fine-tuning process ensures strong translation performance.
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Please find more details in their [paper](https://arxiv.org/abs/2309.11674).
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```
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