QuantFactory/miscii-14b-1028-GGUF

language:

• —en
• —zh license: apache-2.0 library_name: transformers tags:
• —chat
• —conversational
• —custom-research
• —rp
• —roleplay
• —tool-use base_model:
• —Qwen/Qwen2.5-14B-Instruct pipeline_tag: text-generation model-index:
• —name: miscii-14b-1028 results:
• —task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: numfewshot: 0 metrics:
• —type: instlevelstrictacc and promptlevelstrictacc value: 82.37 name: strict accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?query=sthenno-com/miscii-14b-1028 name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: numfewshot: 3 metrics:
• —type: accnorm value: 49.26 name: normalized accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/openllm_leaderboard?query=sthenno-com/miscii-14b-1028 name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competitionmath args: numfew_shot: 4 metrics:
• —type: exactmatch value: 6.34 name: exact match source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/openllm_leaderboard?query=sthenno-com/miscii-14b-1028 name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: numfewshot: 0 metrics:
• —type: accnorm value: 14.21 name: accnorm source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?query=sthenno-com/miscii-14b-1028 name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: numfewshot: 0 metrics:
• —type: accnorm value: 12 name: accnorm source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?query=sthenno-com/miscii-14b-1028 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: numfewshot: 5 metrics:
• —type: acc value: 46.14 name: accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?query=sthenno-com/miscii-14b-1028 name: Open LLM Leaderboard datasets:
• —nvidia/HelpSteer2
• —google/Synthetic-Persona-Chat
• —mlabonne/orpo-dpo-mix-40k new_version: sthenno-com/miscii-14b-1225


QuantFactory/miscii-14b-1028-GGUF

This is quantized version of sthenno-com/miscii-14b-1028 created using llama.cpp

Original Model Card

miscii-14b-1028

Role-based Instructions

Just parse the following as your system prompt. Note there is NO special-tokens here.

An example system prompt:

system_prompt: str = (
    """<|context_start|>personas<|context_sep|>
<|persona_start|>user<|persona_sep|>
{user_persona}<|persona_end|>
<|persona_start|>assistant<|persona_sep|>
{assistant_persona}<|persona_end|><|context_end|>""".format(
        user_persona="""I am Miscii.
I am the designer of Sthenno.
[Optional: Additional statements]""",
        assistant_persona="""I am Sthenno.
I speak in Chinese.
[Optional: Additional statements]""",
    )
)

Training

See Report for miscii-1020 for more details.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here.

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