--- license: apache-2.0 library_name: transformers datasets: - vicgalle/configurable-system-prompt-multitask tags: - TensorBlock - GGUF base_model: vicgalle/ConfigurableHermes-7B model-index: - name: ConfigurableHermes-7B results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 66.04 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/ConfigurableHermes-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 84.31 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/ConfigurableHermes-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 62.44 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/ConfigurableHermes-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 61.71 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/ConfigurableHermes-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 77.43 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/ConfigurableHermes-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 61.41 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/ConfigurableHermes-7B name: Open LLM Leaderboard - 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: 54.11 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vicgalle/ConfigurableHermes-7B 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: 23.16 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vicgalle/ConfigurableHermes-7B 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: 4.31 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vicgalle/ConfigurableHermes-7B 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: 3.58 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vicgalle/ConfigurableHermes-7B 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: 9.11 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vicgalle/ConfigurableHermes-7B 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: 22.5 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vicgalle/ConfigurableHermes-7B name: Open LLM Leaderboard ---
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## vicgalle/ConfigurableHermes-7B - GGUF This repo contains GGUF format model files for [vicgalle/ConfigurableHermes-7B](https://huggingface.co/vicgalle/ConfigurableHermes-7B). 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 | | -------- | ---------- | --------- | ----------- | | [ConfigurableHermes-7B-Q2_K.gguf](https://huggingface.co/tensorblock/ConfigurableHermes-7B-GGUF/tree/main/ConfigurableHermes-7B-Q2_K.gguf) | Q2_K | 2.533 GB | smallest, significant quality loss - not recommended for most purposes | | [ConfigurableHermes-7B-Q3_K_S.gguf](https://huggingface.co/tensorblock/ConfigurableHermes-7B-GGUF/tree/main/ConfigurableHermes-7B-Q3_K_S.gguf) | Q3_K_S | 2.947 GB | very small, high quality loss | | [ConfigurableHermes-7B-Q3_K_M.gguf](https://huggingface.co/tensorblock/ConfigurableHermes-7B-GGUF/tree/main/ConfigurableHermes-7B-Q3_K_M.gguf) | Q3_K_M | 3.277 GB | very small, high quality loss | | [ConfigurableHermes-7B-Q3_K_L.gguf](https://huggingface.co/tensorblock/ConfigurableHermes-7B-GGUF/tree/main/ConfigurableHermes-7B-Q3_K_L.gguf) | Q3_K_L | 3.560 GB | small, substantial quality loss | | [ConfigurableHermes-7B-Q4_0.gguf](https://huggingface.co/tensorblock/ConfigurableHermes-7B-GGUF/tree/main/ConfigurableHermes-7B-Q4_0.gguf) | Q4_0 | 3.827 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [ConfigurableHermes-7B-Q4_K_S.gguf](https://huggingface.co/tensorblock/ConfigurableHermes-7B-GGUF/tree/main/ConfigurableHermes-7B-Q4_K_S.gguf) | Q4_K_S | 3.856 GB | small, greater quality loss | | [ConfigurableHermes-7B-Q4_K_M.gguf](https://huggingface.co/tensorblock/ConfigurableHermes-7B-GGUF/tree/main/ConfigurableHermes-7B-Q4_K_M.gguf) | Q4_K_M | 4.068 GB | medium, balanced quality - recommended | | [ConfigurableHermes-7B-Q5_0.gguf](https://huggingface.co/tensorblock/ConfigurableHermes-7B-GGUF/tree/main/ConfigurableHermes-7B-Q5_0.gguf) | Q5_0 | 4.654 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [ConfigurableHermes-7B-Q5_K_S.gguf](https://huggingface.co/tensorblock/ConfigurableHermes-7B-GGUF/tree/main/ConfigurableHermes-7B-Q5_K_S.gguf) | Q5_K_S | 4.654 GB | large, low quality loss - recommended | | [ConfigurableHermes-7B-Q5_K_M.gguf](https://huggingface.co/tensorblock/ConfigurableHermes-7B-GGUF/tree/main/ConfigurableHermes-7B-Q5_K_M.gguf) | Q5_K_M | 4.779 GB | large, very low quality loss - recommended | | [ConfigurableHermes-7B-Q6_K.gguf](https://huggingface.co/tensorblock/ConfigurableHermes-7B-GGUF/tree/main/ConfigurableHermes-7B-Q6_K.gguf) | Q6_K | 5.534 GB | very large, extremely low quality loss | | [ConfigurableHermes-7B-Q8_0.gguf](https://huggingface.co/tensorblock/ConfigurableHermes-7B-GGUF/tree/main/ConfigurableHermes-7B-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/ConfigurableHermes-7B-GGUF --include "ConfigurableHermes-7B-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/ConfigurableHermes-7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```