QuantFactory/Q2.5-Veltha-14B-0.5-GGUF

library_name: transformers tags:

• —mergekit
• —merge base_model:
• —arcee-ai/SuperNova-Medius
• —huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
• —allura-org/TQ2.5-14B-Aletheia-v1
• —EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2
• —v000000/Qwen2.5-Lumen-14B model-index:
• —name: Q2.5-Veltha-14B-0.5 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: 77.96 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?query=djuna/Q2.5-Veltha-14B-0.5 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: 50.32 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/openllm_leaderboard?query=djuna/Q2.5-Veltha-14B-0.5 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: 33.84 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/openllm_leaderboard?query=djuna/Q2.5-Veltha-14B-0.5 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: 15.77 name: accnorm source: url: https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?query=djuna/Q2.5-Veltha-14B-0.5 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: 14.17 name: accnorm source: url: https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?query=djuna/Q2.5-Veltha-14B-0.5 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: 47.72 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?query=djuna/Q2.5-Veltha-14B-0.5 name: Open LLM Leaderboard


QuantFactory/Q2.5-Veltha-14B-0.5-GGUF

This is quantized version of djuna/Q2.5-Veltha-14B-0.5 created using llama.cpp

Original Model Card

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the della_linear merge method using arcee-ai/SuperNova-Medius as a base.

Models Merged

The following models were included in the merge:

• —huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
• —allura-org/TQ2.5-14B-Aletheia-v1
• —EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2
• —v000000/Qwen2.5-Lumen-14B

Configuration

The following YAML configuration was used to produce this model:

merge_method: della_linear
dtype: float32
out_dtype: bfloat16
parameters:
  epsilon: 0.04
  lambda: 1.05
  normalize: true
base_model: arcee-ai/SuperNova-Medius
tokenizer_source: arcee-ai/SuperNova-Medius
models:
  - model: arcee-ai/SuperNova-Medius
    parameters:
      weight: 10
      density: 1
  - model: EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2
    parameters:
      weight: 7
      density: 0.5
  - model: v000000/Qwen2.5-Lumen-14B
    parameters:
      weight: 7
      density: 0.4
  - model: allura-org/TQ2.5-14B-Aletheia-v1
    parameters:
      weight: 8
      density: 0.4
  - model: huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
    parameters:
      weight: 8
      density: 0.45

Open LLM Leaderboard Evaluation Results

Detailed results can be found here