--- license: gemma library_name: transformers tags: - gemma-2 - TensorBlock - GGUF base_model: anthracite-org/magnum-v3-27b-kto pipeline_tag: text-generation model-index: - name: magnum-v3-27b-kto results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 56.75 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-27b-kto name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 41.16 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-27b-kto name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 15.48 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-27b-kto name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 14.09 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-27b-kto name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 9.92 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-27b-kto name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 35.98 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-27b-kto name: Open LLM Leaderboard ---
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## anthracite-org/magnum-v3-27b-kto - GGUF This repo contains GGUF format model files for [anthracite-org/magnum-v3-27b-kto](https://huggingface.co/anthracite-org/magnum-v3-27b-kto). 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). ## Prompt template ``` <|im_start|>system {system_prompt}<|im_end|> <|im_start|>user {prompt}<|im_end|> <|im_start|>assistant ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [magnum-v3-27b-kto-Q2_K.gguf](https://huggingface.co/tensorblock/magnum-v3-27b-kto-GGUF/tree/main/magnum-v3-27b-kto-Q2_K.gguf) | Q2_K | 9.732 GB | smallest, significant quality loss - not recommended for most purposes | | [magnum-v3-27b-kto-Q3_K_S.gguf](https://huggingface.co/tensorblock/magnum-v3-27b-kto-GGUF/tree/main/magnum-v3-27b-kto-Q3_K_S.gguf) | Q3_K_S | 11.333 GB | very small, high quality loss | | [magnum-v3-27b-kto-Q3_K_M.gguf](https://huggingface.co/tensorblock/magnum-v3-27b-kto-GGUF/tree/main/magnum-v3-27b-kto-Q3_K_M.gguf) | Q3_K_M | 12.503 GB | very small, high quality loss | | [magnum-v3-27b-kto-Q3_K_L.gguf](https://huggingface.co/tensorblock/magnum-v3-27b-kto-GGUF/tree/main/magnum-v3-27b-kto-Q3_K_L.gguf) | Q3_K_L | 13.522 GB | small, substantial quality loss | | [magnum-v3-27b-kto-Q4_0.gguf](https://huggingface.co/tensorblock/magnum-v3-27b-kto-GGUF/tree/main/magnum-v3-27b-kto-Q4_0.gguf) | Q4_0 | 14.555 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [magnum-v3-27b-kto-Q4_K_S.gguf](https://huggingface.co/tensorblock/magnum-v3-27b-kto-GGUF/tree/main/magnum-v3-27b-kto-Q4_K_S.gguf) | Q4_K_S | 14.658 GB | small, greater quality loss | | [magnum-v3-27b-kto-Q4_K_M.gguf](https://huggingface.co/tensorblock/magnum-v3-27b-kto-GGUF/tree/main/magnum-v3-27b-kto-Q4_K_M.gguf) | Q4_K_M | 15.502 GB | medium, balanced quality - recommended | | [magnum-v3-27b-kto-Q5_0.gguf](https://huggingface.co/tensorblock/magnum-v3-27b-kto-GGUF/tree/main/magnum-v3-27b-kto-Q5_0.gguf) | Q5_0 | 17.587 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [magnum-v3-27b-kto-Q5_K_S.gguf](https://huggingface.co/tensorblock/magnum-v3-27b-kto-GGUF/tree/main/magnum-v3-27b-kto-Q5_K_S.gguf) | Q5_K_S | 17.587 GB | large, low quality loss - recommended | | [magnum-v3-27b-kto-Q5_K_M.gguf](https://huggingface.co/tensorblock/magnum-v3-27b-kto-GGUF/tree/main/magnum-v3-27b-kto-Q5_K_M.gguf) | Q5_K_M | 18.075 GB | large, very low quality loss - recommended | | [magnum-v3-27b-kto-Q6_K.gguf](https://huggingface.co/tensorblock/magnum-v3-27b-kto-GGUF/tree/main/magnum-v3-27b-kto-Q6_K.gguf) | Q6_K | 20.809 GB | very large, extremely low quality loss | | [magnum-v3-27b-kto-Q8_0.gguf](https://huggingface.co/tensorblock/magnum-v3-27b-kto-GGUF/tree/main/magnum-v3-27b-kto-Q8_0.gguf) | Q8_0 | 26.950 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/magnum-v3-27b-kto-GGUF --include "magnum-v3-27b-kto-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/magnum-v3-27b-kto-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```