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README.md
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@@ -29,6 +29,7 @@ SambaLingo-Slovenian-Base is a pretrained Bi-lingual Slovenian and English model
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- **Language(s):** Slovenian, English
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- **Finetuned from model:** [Llama 2](https://huggingface.co/meta-llama/Llama-2-7b-hf)
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- **Try the chat version of this model**: [SambaLingo-chat-space](https://huggingface.co/spaces/sambanovasystems/SambaLingo-chat-space).
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- **Blog Post**: [sambalingo-open-source-language-experts](https://sambanova.ai/blog/sambalingo-open-source-language-experts)
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## Getting Started
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We extended the vocabulary of the base llama model from 32,000 tokens to 57,000 tokens by adding up to 25,000 non-overlapping tokens from the new language.
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## Evaluation
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| | SambaLingo-Slovenian-Base | sl-gpt2 | bloom-7b1 | xglm-7.5B | mGPT-13B |
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|-------------------------------|---------|-----------|-----------|----------|--------|
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| Perplexity (Lower Is Better) | **1.678** | - | 3.261 | 4.201 | 3.428 |
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| FLORES en->sl (8 shot, CHRF) | **0.508** | 0.072 | 0.143 | 0.068 | 0.062 |
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| FLORES sl->en (8 shot, CHRF) | **0.565** | 0.066 | 0.182 | 0.184 | 0.058 |
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| FLORES en->sl (8 shot, BLEU) | **0.202** | 0.000 | 0.004 | 0.152 | 0.000 |
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| FLORES sl->en (8 shot, BLEU) | **0.273** | 0.000 | 0.010 | 0.007 | 0.000 |
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| Belebele (3 shot) | **42.78%** | 26.11% | 23.44% | 23.33% | 23.89% |
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| SIB-200 (3 shot) | **56.37%** | - | 41.18% | 50.00% | 40.69% |
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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## Cite SambaLingo
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```
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@
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}
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```
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- **Language(s):** Slovenian, English
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- **Finetuned from model:** [Llama 2](https://huggingface.co/meta-llama/Llama-2-7b-hf)
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- **Try the chat version of this model**: [SambaLingo-chat-space](https://huggingface.co/spaces/sambanovasystems/SambaLingo-chat-space).
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- **Paper:** [SambaLingo: Teaching Large Language Models New Languages](https://arxiv.org/abs/2404.05829)
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- **Blog Post**: [sambalingo-open-source-language-experts](https://sambanova.ai/blog/sambalingo-open-source-language-experts)
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## Getting Started
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We extended the vocabulary of the base llama model from 32,000 tokens to 57,000 tokens by adding up to 25,000 non-overlapping tokens from the new language.
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## Evaluation
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For evaluation results see our paper: [SambaLingo: Teaching Large Language Models New Languages](https://arxiv.org/abs/2404.05829)
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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## Cite SambaLingo
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```
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@misc{csaki2024sambalingo,
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title={SambaLingo: Teaching Large Language Models New Languages},
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author={Zoltan Csaki and Bo Li and Jonathan Li and Qiantong Xu and Pian Pawakapan and Leon Zhang and Yun Du and Hengyu Zhao and Changran Hu and Urmish Thakker},
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year={2024},
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eprint={2404.05829},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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