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README.md
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@@ -113,18 +113,18 @@ Refer to the Provided Files table below to see what files use which methods, and
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| Name | Quant method | Bits | Size | Max RAM required | Use case |
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| mythalion-13b.Q2_K.gguf | Q2_K | 2 | 5.43 GB| 7.93 GB | smallest, significant quality loss - not recommended for most purposes |
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| mythalion-13b.Q3_K_S.gguf | Q3_K_S | 3 | 5.66 GB| 8.16 GB | very small, high quality loss |
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| mythalion-13b.Q3_K_M.gguf | Q3_K_M | 3 | 6.34 GB| 8.84 GB | very small, high quality loss |
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| mythalion-13b.Q3_K_L.gguf | Q3_K_L | 3 | 6.93 GB| 9.43 GB | small, substantial quality loss |
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| mythalion-13b.Q4_0.gguf | Q4_0 | 4 | 7.37 GB| 9.87 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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| mythalion-13b.Q4_K_S.gguf | Q4_K_S | 4 | 7.41 GB| 9.91 GB | small, greater quality loss |
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| mythalion-13b.Q4_K_M.gguf | Q4_K_M | 4 | 7.87 GB| 10.37 GB | medium, balanced quality - recommended |
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| mythalion-13b.Q5_0.gguf | Q5_0 | 5 | 8.97 GB| 11.47 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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| mythalion-13b.Q5_K_S.gguf | Q5_K_S | 5 | 8.97 GB| 11.47 GB | large, low quality loss - recommended |
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| mythalion-13b.Q5_K_M.gguf | Q5_K_M | 5 | 9.23 GB| 11.73 GB | large, very low quality loss - recommended |
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| mythalion-13b.Q6_K.gguf | Q6_K | 6 | 10.68 GB| 13.18 GB | very large, extremely low quality loss |
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| mythalion-13b.Q8_0.gguf | Q8_0 | 8 | 13.83 GB| 16.33 GB | very large, extremely low quality loss - not recommended |
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**Note**: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
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| Name | Quant method | Bits | Size | Max RAM required | Use case |
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| ---- | ---- | ---- | ---- | ---- | ----- |
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| [mythalion-13b.Q2_K.gguf](https://huggingface.co/TheBloke/Mythalion-13B-GGUF/blob/main/mythalion-13b.Q2_K.gguf) | Q2_K | 2 | 5.43 GB| 7.93 GB | smallest, significant quality loss - not recommended for most purposes |
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| [mythalion-13b.Q3_K_S.gguf](https://huggingface.co/TheBloke/Mythalion-13B-GGUF/blob/main/mythalion-13b.Q3_K_S.gguf) | Q3_K_S | 3 | 5.66 GB| 8.16 GB | very small, high quality loss |
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| [mythalion-13b.Q3_K_M.gguf](https://huggingface.co/TheBloke/Mythalion-13B-GGUF/blob/main/mythalion-13b.Q3_K_M.gguf) | Q3_K_M | 3 | 6.34 GB| 8.84 GB | very small, high quality loss |
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| [mythalion-13b.Q3_K_L.gguf](https://huggingface.co/TheBloke/Mythalion-13B-GGUF/blob/main/mythalion-13b.Q3_K_L.gguf) | Q3_K_L | 3 | 6.93 GB| 9.43 GB | small, substantial quality loss |
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| [mythalion-13b.Q4_0.gguf](https://huggingface.co/TheBloke/Mythalion-13B-GGUF/blob/main/mythalion-13b.Q4_0.gguf) | Q4_0 | 4 | 7.37 GB| 9.87 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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| [mythalion-13b.Q4_K_S.gguf](https://huggingface.co/TheBloke/Mythalion-13B-GGUF/blob/main/mythalion-13b.Q4_K_S.gguf) | Q4_K_S | 4 | 7.41 GB| 9.91 GB | small, greater quality loss |
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| [mythalion-13b.Q4_K_M.gguf](https://huggingface.co/TheBloke/Mythalion-13B-GGUF/blob/main/mythalion-13b.Q4_K_M.gguf) | Q4_K_M | 4 | 7.87 GB| 10.37 GB | medium, balanced quality - recommended |
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| [mythalion-13b.Q5_0.gguf](https://huggingface.co/TheBloke/Mythalion-13B-GGUF/blob/main/mythalion-13b.Q5_0.gguf) | Q5_0 | 5 | 8.97 GB| 11.47 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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| [mythalion-13b.Q5_K_S.gguf](https://huggingface.co/TheBloke/Mythalion-13B-GGUF/blob/main/mythalion-13b.Q5_K_S.gguf) | Q5_K_S | 5 | 8.97 GB| 11.47 GB | large, low quality loss - recommended |
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| [mythalion-13b.Q5_K_M.gguf](https://huggingface.co/TheBloke/Mythalion-13B-GGUF/blob/main/mythalion-13b.Q5_K_M.gguf) | Q5_K_M | 5 | 9.23 GB| 11.73 GB | large, very low quality loss - recommended |
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| [mythalion-13b.Q6_K.gguf](https://huggingface.co/TheBloke/Mythalion-13B-GGUF/blob/main/mythalion-13b.Q6_K.gguf) | Q6_K | 6 | 10.68 GB| 13.18 GB | very large, extremely low quality loss |
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| [mythalion-13b.Q8_0.gguf](https://huggingface.co/TheBloke/Mythalion-13B-GGUF/blob/main/mythalion-13b.Q8_0.gguf) | Q8_0 | 8 | 13.83 GB| 16.33 GB | very large, extremely low quality loss - not recommended |
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**Note**: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
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