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@@ -254,6 +254,26 @@ All quants made using imatrix option with dataset provided by Kalomaze [here](ht
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  | [Meta-Llama-3-70B-Instruct-IQ1_M.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-IQ1_M.gguf) | IQ1_M | 16.75GB | Extremely low quality, *not* recommended. |
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  | [Meta-Llama-3-70B-Instruct-IQ1_S.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-IQ1_S.gguf) | IQ1_S | 15.34GB | Extremely low quality, *not* recommended. |
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  ## Which file should I choose?
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  A great write up with charts showing various performances is provided by Artefact2 [here](https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9)
 
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  | [Meta-Llama-3-70B-Instruct-IQ1_M.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-IQ1_M.gguf) | IQ1_M | 16.75GB | Extremely low quality, *not* recommended. |
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  | [Meta-Llama-3-70B-Instruct-IQ1_S.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-IQ1_S.gguf) | IQ1_S | 15.34GB | Extremely low quality, *not* recommended. |
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+ ## Downloading using huggingface-cli
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+ First, make sure you have hugginface-cli installed:
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+ ```
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+ pip install -U "huggingface_hub[cli]"
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+ ```
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+ Then, you can target the specific file you want:
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+ ```
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+ huggingface-cli download bartowski/Meta-Llama-3-70B-Instruct-GGUF --include "Meta-Llama-3-70B-Instruct-Q4_K_M.gguf" Meta-Llama-3-70B-Instruct-Q4_K_M.gguf --local-dir-use-symlinks False
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+ ```
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+ If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:
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+ ```
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+ huggingface-cli download bartowski/Meta-Llama-3-70B-Instruct-GGUF --include "Meta-Llama-3-70B-Instruct-Q8_0.gguf/*" Meta-Llama-3-70B-Instruct-Q8_0.gguf --local-dir-use-symlinks False
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+ ```
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+
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  ## Which file should I choose?
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  A great write up with charts showing various performances is provided by Artefact2 [here](https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9)