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auto-patch README.md

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  1. README.md +10 -1
README.md CHANGED
@@ -40,12 +40,21 @@ more details, including on how to concatenate multi-part files.
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q3_K_M.gguf) | Q3_K_M | 16.0 | lower quality |
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q3_K_L.gguf) | Q3_K_L | 17.3 | |
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.IQ4_XS.gguf) | IQ4_XS | 18.0 | |
 
 
 
 
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q4_K_S.gguf) | Q4_K_S | 18.9 | fast, recommended |
 
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q4_K_M.gguf) | Q4_K_M | 20.0 | fast, recommended |
 
 
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q5_K_S.gguf) | Q5_K_S | 22.7 | |
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q5_K_M.gguf) | Q5_K_M | 23.4 | |
 
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q6_K.gguf) | Q6_K | 27.0 | very good quality |
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q8_0.gguf) | Q8_0 | 34.9 | fast, best quality |
 
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  Here is a handy graph by ikawrakow comparing some lower-quality quant
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  types (lower is better):
@@ -64,6 +73,6 @@ questions you might have and/or if you want some other model quantized.
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  I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
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  me use its servers and providing upgrades to my workstation to enable
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- this work in my free time.
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  <!-- end -->
 
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q3_K_M.gguf) | Q3_K_M | 16.0 | lower quality |
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q3_K_L.gguf) | Q3_K_L | 17.3 | |
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.IQ4_XS.gguf) | IQ4_XS | 18.0 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q4_0.gguf) | Q4_0 | 18.7 | fast, low quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q4_0_4_4.gguf) | Q4_0_4_4 | 18.7 | fast on arm, low quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q4_0_4_8.gguf) | Q4_0_4_8 | 18.7 | fast on arm+i8mm, low quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q4_0_8_8.gguf) | Q4_0_8_8 | 18.7 | fast on arm+sve, low quality |
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q4_K_S.gguf) | Q4_K_S | 18.9 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.IQ4_NL.gguf) | IQ4_NL | 18.9 | prefer IQ4_XS |
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q4_K_M.gguf) | Q4_K_M | 20.0 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q4_1.gguf) | Q4_1 | 20.7 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q5_0.gguf) | Q5_0 | 22.7 | |
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q5_K_S.gguf) | Q5_K_S | 22.7 | |
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q5_K_M.gguf) | Q5_K_M | 23.4 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q5_1.gguf) | Q5_1 | 24.7 | |
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q6_K.gguf) | Q6_K | 27.0 | very good quality |
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  | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.Q8_0.gguf) | Q8_0 | 34.9 | fast, best quality |
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+ | [PART 1](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.SOURCE.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-GGUF/resolve/main/Qwen2.5-32B-Instruct.SOURCE.gguf.part2of2) | SOURCE | 65.6 | source gguf, only provided when it was hard to come by |
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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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  I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
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  me use its servers and providing upgrades to my workstation to enable
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+ this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
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  <!-- end -->