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README.md
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@@ -51,13 +51,13 @@ The key benefit of GGUF is that it is a extensible, future-proof format which st
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Here are a list of clients and libraries that are known to support GGUF:
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* [llama.cpp](https://github.com/ggerganov/llama.cpp).
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* [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI
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* [KoboldCpp](https://github.com/LostRuins/koboldcpp),
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* [LM Studio](https://lmstudio.ai/),
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* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui),
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* [ctransformers](https://github.com/marella/ctransformers),
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* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python),
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* [candle](https://github.com/huggingface/candle),
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<!-- README_GGUF.md-about-gguf end -->
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<!-- repositories-available start -->
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@@ -132,7 +132,7 @@ Make sure you are using `llama.cpp` from commit [6381d4e110bd0ec02843a60bbeb8b6f
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For compatibility with older versions of llama.cpp, or for any third-party libraries or clients that haven't yet updated for GGUF, please use GGML files instead.
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```
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./main -t 10 -ngl 32 -m llama-2-7b.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "
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```
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Change `-t 10` to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use `-t 8`. If offloading all layers to GPU, set `-t 1`.
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Here are a list of clients and libraries that are known to support GGUF:
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* [llama.cpp](https://github.com/ggerganov/llama.cpp).
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* [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI, with many features and powerful extensions.
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* [KoboldCpp](https://github.com/LostRuins/koboldcpp), a fully featured web UI, with full GPU accel across multiple platforms and GPU architectures. Especially good for story telling.
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* [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI with GPU acceleration on both Windows (NVidia and AMD), and macOS.
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* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), a great web UI with many interesting and unique features, including a full model library for easy model selection.
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* [ctransformers](https://github.com/marella/ctransformers), a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server.
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* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
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* [candle](https://github.com/huggingface/candle), a Rust ML framework with a focus on performance, including GPU support, and ease of use.
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<!-- README_GGUF.md-about-gguf end -->
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<!-- repositories-available start -->
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For compatibility with older versions of llama.cpp, or for any third-party libraries or clients that haven't yet updated for GGUF, please use GGML files instead.
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```
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./main -t 10 -ngl 32 -m llama-2-7b.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "{prompt}"
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```
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Change `-t 10` to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use `-t 8`. If offloading all layers to GPU, set `-t 1`.
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