Text Generation
Transformers
PyTorch
Thai
English
llama
conversational
text-generation-inference
Inference Endpoints
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@@ -26,7 +26,6 @@ SambaLingo-Thai-Chat-70B is a human aligned chat model trained in Thai and Engli
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  - **Model type:** Language Model
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  - **Language(s):** Thai, English
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  - **Finetuned from model:** [Llama-2-70b](https://huggingface.co/meta-llama/Llama-2-70b-hf)
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- - **Try 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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@@ -84,6 +83,9 @@ The DPO phase was done on the [ultrafeedback](https://huggingface.co/datasets/Hu
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  ## Tokenizer Details
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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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  ## 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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@@ -126,13 +128,13 @@ We would like to give a special thanks to the following groups:
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  ## Cite SambaLingo
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  ```
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- @software{sambalingo,
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- title = {{SambaLingo: Open Source Language Experts}},
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- author = {SambaNova Systems},
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- url = {https://huggingface.co/sambanovasystems/SambaLingo-Thai-Chat-70B}
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- month = {2},
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- year = {2024},
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- version = {1.0},
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  }
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  ```
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  - **Model type:** Language Model
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  - **Language(s):** Thai, English
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  - **Finetuned from model:** [Llama-2-70b](https://huggingface.co/meta-llama/Llama-2-70b-hf)
 
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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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  ## Tokenizer Details
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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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+
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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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