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README.md
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@@ -23,8 +23,16 @@ This repo contains GGUF format model files for [Puluming/AISquare-Instruct-llama
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The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
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## Prompt template
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```
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```
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| Filename | Quant type | File Size | Description |
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| -------- | ---------- | --------- | ----------- |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q2_K.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q3_K_S.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q3_K_M.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q3_K_L.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q4_0.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q4_K_S.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q4_K_M.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q5_0.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q5_K_S.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q5_K_M.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q6_K.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q8_0.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/
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## Downloading instruction
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The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
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<div style="text-align: left; margin: 20px 0;">
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<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
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Run them on the TensorBlock client using your local machine ↗
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</a>
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</div>
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## Prompt template
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```
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```
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| Filename | Quant type | File Size | Description |
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| -------- | ---------- | --------- | ----------- |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q2_K.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/blob/main/AISquare-Instruct-llama2-koen-13b-v0.9.18-Q2_K.gguf) | Q2_K | 4.600 GB | smallest, significant quality loss - not recommended for most purposes |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q3_K_S.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/blob/main/AISquare-Instruct-llama2-koen-13b-v0.9.18-Q3_K_S.gguf) | Q3_K_S | 5.356 GB | very small, high quality loss |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q3_K_M.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/blob/main/AISquare-Instruct-llama2-koen-13b-v0.9.18-Q3_K_M.gguf) | Q3_K_M | 5.988 GB | very small, high quality loss |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q3_K_L.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/blob/main/AISquare-Instruct-llama2-koen-13b-v0.9.18-Q3_K_L.gguf) | Q3_K_L | 6.539 GB | small, substantial quality loss |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q4_0.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/blob/main/AISquare-Instruct-llama2-koen-13b-v0.9.18-Q4_0.gguf) | Q4_0 | 6.955 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q4_K_S.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/blob/main/AISquare-Instruct-llama2-koen-13b-v0.9.18-Q4_K_S.gguf) | Q4_K_S | 7.008 GB | small, greater quality loss |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q4_K_M.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/blob/main/AISquare-Instruct-llama2-koen-13b-v0.9.18-Q4_K_M.gguf) | Q4_K_M | 7.421 GB | medium, balanced quality - recommended |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q5_0.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/blob/main/AISquare-Instruct-llama2-koen-13b-v0.9.18-Q5_0.gguf) | Q5_0 | 8.459 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q5_K_S.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/blob/main/AISquare-Instruct-llama2-koen-13b-v0.9.18-Q5_K_S.gguf) | Q5_K_S | 8.459 GB | large, low quality loss - recommended |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q5_K_M.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/blob/main/AISquare-Instruct-llama2-koen-13b-v0.9.18-Q5_K_M.gguf) | Q5_K_M | 8.699 GB | large, very low quality loss - recommended |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q6_K.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/blob/main/AISquare-Instruct-llama2-koen-13b-v0.9.18-Q6_K.gguf) | Q6_K | 10.058 GB | very large, extremely low quality loss |
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| [AISquare-Instruct-llama2-koen-13b-v0.9.18-Q8_0.gguf](https://huggingface.co/tensorblock/AISquare-Instruct-llama2-koen-13b-v0.9.18-GGUF/blob/main/AISquare-Instruct-llama2-koen-13b-v0.9.18-Q8_0.gguf) | Q8_0 | 13.027 GB | very large, extremely low quality loss - not recommended |
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## Downloading instruction
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