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README.md
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@@ -34,7 +34,7 @@ This is a DOI repository, created 26th June 2023. It contains the GGML model fil
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The purpose of a DOI repository is to provide a permanent record of a set of files, guaranteed not to change. Therefore the GGML files in this repository will never update.
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## Repositories available
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| selfee-13b.ggmlv3.q6_K.bin | q6_K | 6 | 10.68 GB | 13.18 GB | New k-quant method. Uses GGML_TYPE_Q8_K - 6-bit quantization - for all tensors |
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| selfee-13b.ggmlv3.q8_0.bin | q8_0 | 8 | 13.83 GB | 16.33 GB | Original llama.cpp quant method, 8-bit. Almost indistinguishable from float16. High resource use and slow. Not recommended for most users. |
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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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## How to run in `llama.cpp`
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The purpose of a DOI repository is to provide a permanent record of a set of files, guaranteed not to change. Therefore the GGML files in this repository will never update.
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If you're looking for the latest GGMLs for Selfee 13B GGML, please check [TheBloke/Selfee-13B-GGML](https://huggingface.co/TheBloke/Selfee-13B-GGML).
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## Repositories available
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| selfee-13b.ggmlv3.q6_K.bin | q6_K | 6 | 10.68 GB | 13.18 GB | New k-quant method. Uses GGML_TYPE_Q8_K - 6-bit quantization - for all tensors |
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| selfee-13b.ggmlv3.q8_0.bin | q8_0 | 8 | 13.83 GB | 16.33 GB | Original llama.cpp quant method, 8-bit. Almost indistinguishable from float16. High resource use and slow. Not recommended for most users. |
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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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## How to run in `llama.cpp`
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