--- base_model: Kabster/BioMistral-Zephyr-Beta-SLERP tags: - mergekit - merge - TensorBlock - GGUF license: apache-2.0 ---
TensorBlock
[![Website](https://img.shields.io/badge/Website-tensorblock.co-blue?logo=google-chrome&logoColor=white)](https://tensorblock.co) [![Twitter](https://img.shields.io/twitter/follow/tensorblock_aoi?style=social)](https://twitter.com/tensorblock_aoi) [![Discord](https://img.shields.io/badge/Discord-Join%20Us-5865F2?logo=discord&logoColor=white)](https://discord.gg/Ej5NmeHFf2) [![GitHub](https://img.shields.io/badge/GitHub-TensorBlock-black?logo=github&logoColor=white)](https://github.com/TensorBlock) [![Telegram](https://img.shields.io/badge/Telegram-Group-blue?logo=telegram)](https://t.me/TensorBlock) ## Kabster/BioMistral-Zephyr-Beta-SLERP - GGUF This repo contains GGUF format model files for [Kabster/BioMistral-Zephyr-Beta-SLERP](https://huggingface.co/Kabster/BioMistral-Zephyr-Beta-SLERP). 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). ## Our projects
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## Prompt template ``` [INST] {prompt} [/INST] ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [BioMistral-Zephyr-Beta-SLERP-Q2_K.gguf](https://huggingface.co/tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF/blob/main/BioMistral-Zephyr-Beta-SLERP-Q2_K.gguf) | Q2_K | 2.532 GB | smallest, significant quality loss - not recommended for most purposes | | [BioMistral-Zephyr-Beta-SLERP-Q3_K_S.gguf](https://huggingface.co/tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF/blob/main/BioMistral-Zephyr-Beta-SLERP-Q3_K_S.gguf) | Q3_K_S | 2.947 GB | very small, high quality loss | | [BioMistral-Zephyr-Beta-SLERP-Q3_K_M.gguf](https://huggingface.co/tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF/blob/main/BioMistral-Zephyr-Beta-SLERP-Q3_K_M.gguf) | Q3_K_M | 3.277 GB | very small, high quality loss | | [BioMistral-Zephyr-Beta-SLERP-Q3_K_L.gguf](https://huggingface.co/tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF/blob/main/BioMistral-Zephyr-Beta-SLERP-Q3_K_L.gguf) | Q3_K_L | 3.560 GB | small, substantial quality loss | | [BioMistral-Zephyr-Beta-SLERP-Q4_0.gguf](https://huggingface.co/tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF/blob/main/BioMistral-Zephyr-Beta-SLERP-Q4_0.gguf) | Q4_0 | 3.827 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [BioMistral-Zephyr-Beta-SLERP-Q4_K_S.gguf](https://huggingface.co/tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF/blob/main/BioMistral-Zephyr-Beta-SLERP-Q4_K_S.gguf) | Q4_K_S | 3.856 GB | small, greater quality loss | | [BioMistral-Zephyr-Beta-SLERP-Q4_K_M.gguf](https://huggingface.co/tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF/blob/main/BioMistral-Zephyr-Beta-SLERP-Q4_K_M.gguf) | Q4_K_M | 4.068 GB | medium, balanced quality - recommended | | [BioMistral-Zephyr-Beta-SLERP-Q5_0.gguf](https://huggingface.co/tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF/blob/main/BioMistral-Zephyr-Beta-SLERP-Q5_0.gguf) | Q5_0 | 4.654 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [BioMistral-Zephyr-Beta-SLERP-Q5_K_S.gguf](https://huggingface.co/tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF/blob/main/BioMistral-Zephyr-Beta-SLERP-Q5_K_S.gguf) | Q5_K_S | 4.654 GB | large, low quality loss - recommended | | [BioMistral-Zephyr-Beta-SLERP-Q5_K_M.gguf](https://huggingface.co/tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF/blob/main/BioMistral-Zephyr-Beta-SLERP-Q5_K_M.gguf) | Q5_K_M | 4.779 GB | large, very low quality loss - recommended | | [BioMistral-Zephyr-Beta-SLERP-Q6_K.gguf](https://huggingface.co/tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF/blob/main/BioMistral-Zephyr-Beta-SLERP-Q6_K.gguf) | Q6_K | 5.534 GB | very large, extremely low quality loss | | [BioMistral-Zephyr-Beta-SLERP-Q8_0.gguf](https://huggingface.co/tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF/blob/main/BioMistral-Zephyr-Beta-SLERP-Q8_0.gguf) | Q8_0 | 7.167 GB | very large, extremely low quality loss - not recommended | ## Downloading instruction ### Command line Firstly, install Huggingface Client ```shell pip install -U "huggingface_hub[cli]" ``` Then, downoad the individual model file the a local directory ```shell huggingface-cli download tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF --include "BioMistral-Zephyr-Beta-SLERP-Q2_K.gguf" --local-dir MY_LOCAL_DIR ``` If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try: ```shell huggingface-cli download tensorblock/BioMistral-Zephyr-Beta-SLERP-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```