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  # Meta's LLaMa 30B GGML
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- These files are GGML format model files for [Meta's LLaMa 30B](https://huggingface.co/https://ai.facebook.com/blog/large-language-model-llama-meta-ai/).
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  GGML files are for CPU + GPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp) and libraries and UIs which support this format, such as:
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  * [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
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  ## Repositories available
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- * [4-bit GPTQ models for GPU inference](https://huggingface.co/none)
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  * [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference](https://huggingface.co/TheBloke/llama-30B-GGML)
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  * [Unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/huggyllama/llama-30b)
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  Thank you to all my generous patrons and donaters!
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  <!-- footer end -->
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- # Original model card: Meta's LLaMa 30B
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  # Meta's LLaMa 30B GGML
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+ These files are GGML format model files for [Meta's LLaMa 30B](https://ai.facebook.com/blog/large-language-model-llama-meta-ai/).
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  GGML files are for CPU + GPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp) and libraries and UIs which support this format, such as:
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  * [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
 
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  ## Repositories available
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  * [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference](https://huggingface.co/TheBloke/llama-30B-GGML)
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  * [Unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/huggyllama/llama-30b)
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  Thank you to all my generous patrons and donaters!
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  <!-- footer end -->