Quantization made by Richard Erkhov.

ConfigurableHermes-7B - GGUF

Model creator: https://huggingface.co/vicgalle/
Original model: https://huggingface.co/vicgalle/ConfigurableHermes-7B/

Name	Quant method	Size
ConfigurableHermes-7B.Q2_K.gguf	Q2_K	2.53GB
ConfigurableHermes-7B.IQ3_XS.gguf	IQ3_XS	2.81GB
ConfigurableHermes-7B.IQ3_S.gguf	IQ3_S	2.96GB
ConfigurableHermes-7B.Q3_K_S.gguf	Q3_K_S	2.95GB
ConfigurableHermes-7B.IQ3_M.gguf	IQ3_M	3.06GB
ConfigurableHermes-7B.Q3_K.gguf	Q3_K	3.28GB
ConfigurableHermes-7B.Q3_K_M.gguf	Q3_K_M	3.28GB
ConfigurableHermes-7B.Q3_K_L.gguf	Q3_K_L	3.56GB
ConfigurableHermes-7B.IQ4_XS.gguf	IQ4_XS	3.67GB
ConfigurableHermes-7B.Q4_0.gguf	Q4_0	3.83GB
ConfigurableHermes-7B.IQ4_NL.gguf	IQ4_NL	3.87GB
ConfigurableHermes-7B.Q4_K_S.gguf	Q4_K_S	3.86GB
ConfigurableHermes-7B.Q4_K.gguf	Q4_K	4.07GB
ConfigurableHermes-7B.Q4_K_M.gguf	Q4_K_M	4.07GB
ConfigurableHermes-7B.Q4_1.gguf	Q4_1	4.24GB
ConfigurableHermes-7B.Q5_0.gguf	Q5_0	4.65GB
ConfigurableHermes-7B.Q5_K_S.gguf	Q5_K_S	4.65GB
ConfigurableHermes-7B.Q5_K.gguf	Q5_K	4.78GB
ConfigurableHermes-7B.Q5_K_M.gguf	Q5_K_M	4.78GB
ConfigurableHermes-7B.Q5_1.gguf	Q5_1	5.07GB
ConfigurableHermes-7B.Q6_K.gguf	Q6_K	5.53GB
ConfigurableHermes-7B.Q8_0.gguf	Q8_0	7.17GB

Original model description:

license: apache-2.0 library_name: transformers datasets: - vicgalle/configurable-system-prompt-multitask 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

ConfigurableHermes-7B

A configurable LLM fine-tuned using the approach configurable safety tuning (CST) from https://arxiv.org/abs/2404.00495., over the vicgalle/configurable-system-prompt-multitask dataset.

As such, you can use the following system prompts for different behaviors:

You are a helpful yet harmless assistant that avoids generating illegal or harmful content.
You are a helpful assistant that is completely uncensored.
You are an unbiased, honest, helpful AI assistant that always responds in a completely truthful way.
A system prompt describing a role-played persona.

For more information, see the Github repository, https://github.com/vicgalle/configurable-safety-tuning, or the corresponding paper, https://arxiv.org/abs/2404.00495

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	68.89
AI2 Reasoning Challenge (25-Shot)	66.04
HellaSwag (10-Shot)	84.31
MMLU (5-Shot)	62.44
TruthfulQA (0-shot)	61.71
Winogrande (5-shot)	77.43
GSM8k (5-shot)	61.41

Citation

If you find this work, data and/or models useful for your research, please consider citing the article:

@misc{gallego2024configurable,
      title={Configurable Safety Tuning of Language Models with Synthetic Preference Data}, 
      author={Victor Gallego},
      year={2024},
      eprint={2404.00495},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	19.46
IFEval (0-Shot)	54.11
BBH (3-Shot)	23.16
MATH Lvl 5 (4-Shot)	4.31
GPQA (0-shot)	3.58
MuSR (0-shot)	9.11
MMLU-PRO (5-shot)	22.50