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88d98ad
auto-patch README.md
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README.md
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@@ -31,12 +31,27 @@ more details, including on how to concatenate multi-part files.
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| Link | Type | Size/GB | Notes |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ2_M.gguf) | i1-IQ2_M | 3.0 | |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q2_K.gguf) | i1-Q2_K | 3.3 | IQ3_XXS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.4 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 4.1 | IQ3_S probably better |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.8 | optimal size/speed/quality |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 5.0 | fast, recommended |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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| Link | Type | Size/GB | Notes |
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|:-----|:-----|--------:|:------|
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ1_S.gguf) | i1-IQ1_S | 2.1 | for the desperate |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ1_M.gguf) | i1-IQ1_M | 2.3 | mostly desperate |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ2_S.gguf) | i1-IQ2_S | 2.9 | |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ2_M.gguf) | i1-IQ2_M | 3.0 | |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q2_K.gguf) | i1-Q2_K | 3.3 | IQ3_XXS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.4 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.8 | IQ3_XS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ3_S.gguf) | i1-IQ3_S | 3.8 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ3_M.gguf) | i1-IQ3_M | 3.9 | |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 4.1 | IQ3_S probably better |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.4 | IQ3_M probably better |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q4_0.gguf) | i1-Q4_0 | 4.8 | fast, low quality |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.8 | optimal size/speed/quality |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 5.0 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.8 | |
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| [GGUF](https://huggingface.co/mradermacher/Llama-3-Nerdy-RP-8B-i1-GGUF/resolve/main/Llama-3-Nerdy-RP-8B.i1-Q6_K.gguf) | i1-Q6_K | 6.7 | practically like static Q6_K |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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