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README.md
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@@ -39,8 +39,9 @@ I have quantised the GGML files in this repo with the latest version. Therefore
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| Name | Quant method | Bits | Size | RAM required | Use case |
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`manticore-13B.ggmlv2.q4_0.bin` | q4_0 | 4bit | 8.14GB | 10.5GB | 4-bit. |
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`manticore-13B.ggmlv2.q4_1.bin` |
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`manticore-13B.ggmlv2.q5_0.bin` |
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`manticore-13B.ggmlv2.q8_0.bin` | q8_0 | 8bit | 14.6GB | 17GB | 8-bit. Almost indistinguishable from float16. Huge resource use and slow. Not recommended for normal use. |
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## How to run in `llama.cpp`
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| Name | Quant method | Bits | Size | RAM required | Use case |
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| ---- | ---- | ---- | ---- | ---- | ----- |
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`manticore-13B.ggmlv2.q4_0.bin` | q4_0 | 4bit | 8.14GB | 10.5GB | 4-bit. |
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`manticore-13B.ggmlv2.q4_1.bin` | q4_1 | 4bit | 8.14GB | 10.5GB | 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
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`manticore-13B.ggmlv2.q5_0.bin` | q5_0 | 5bit | 8.95GB | 11.0GB | 5-bit. Higher accuracy, higher resource usage and slower inference. |
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`manticore-13B.ggmlv2.q5_1.bin` | q5_1 | 5bit | 9.76GB | 12.25GB | 5-bit. Even higher accuracy, and higher resource usage and slower inference. |
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`manticore-13B.ggmlv2.q8_0.bin` | q8_0 | 8bit | 14.6GB | 17GB | 8-bit. Almost indistinguishable from float16. Huge resource use and slow. Not recommended for normal use. |
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## How to run in `llama.cpp`
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