Nitral-Archive/Kunocchini-7b

Thanks to @Epiculous for the dope model/ help with llm backends and support overall.

Id like to also thank @kalomaze for the dope sampler additions to ST.

@SanjiWatsuki Thank you very much for the help, and the model!

ST users can find the TextGenPreset in the folder labeled so.

Quants:Thank you @bartowski, @jeiku, @konz00.

https://huggingface.co/bartowski/Kunocchini-exl2

https://huggingface.co/jeiku/Konocchini-7B_GGUF

https://huggingface.co/konz00/Kunocchini-7b-GGUF

The following models were included in the merge:

• SanjiWatsuki/Kunoichi-DPO-v2-7B
• Epiculous/Fett-uccine-7B

Configuration

The following YAML configuration was used to produce this model:

slices:
  - sources:
      - model: SanjiWatsuki/Kunoichi-DPO-v2-7B
        layer_range: [0, 32]
      - model: Epiculous/Fett-uccine-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: SanjiWatsuki/Kunoichi-DPO-v2-7B
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	68.78
AI2 Reasoning Challenge (25-Shot)	67.49
HellaSwag (10-Shot)	86.85
MMLU (5-Shot)	63.89
TruthfulQA (0-shot)	68.62
Winogrande (5-shot)	77.98
GSM8k (5-shot)	47.84