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README.md
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This model was converted to GGUF format from [`Tower-Babel/Babel-9B-Chat`](https://huggingface.co/Tower-Babel/Babel-9B-Chat) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/Tower-Babel/Babel-9B-Chat) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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This model was converted to GGUF format from [`Tower-Babel/Babel-9B-Chat`](https://huggingface.co/Tower-Babel/Babel-9B-Chat) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/Tower-Babel/Babel-9B-Chat) for more details on the model.
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We introduce Babel, a multilingual LLM that covers the top 25 languages by number of speakers, including English, Chinese, Hindi, Spanish, Arabic, French, Bengali, Portuguese, Russian, Urdu, Indonesian, German, Japanese, Swahili, Filipino, Tamil, Vietnamese, Turkish, Italian, Javanese, Korean, Hausa, Persian, Thai, and Burmese. These 25 languages support over 90% of the global population, and include many languages neglected by other open multilingual LLMs. Unlike traditional continued pretraining approaches, Babel expands its parameter count through a layer extension technique that elevates Babel's performance ceiling.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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