Nitral-AI/Kunocchini-7b-128k-test

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 @s3nh! https://huggingface.co./s3nh/Kunocchini-7b-128k-test-GGUF and @bartowski https://huggingface.co./bartowski/Kunocchini-7b-128k-test-exl2 Thanks To @Lewdiculus for the Imatrix gguf quants: https://huggingface.co./Lewdiculous/Kunocchini-7b-128k-test-GGUF-Imatrix

The following models were included in the merge:

• SanjiWatsuki/Kunoichi-DPO-v2-7B
• Epiculous/Fett-uccine-Long-Noodle-7B-120k-Context

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-Long-Noodle-7B-120k-Context
        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.	67.24
AI2 Reasoning Challenge (25-Shot)	66.98
HellaSwag (10-Shot)	85.62
MMLU (5-Shot)	61.27
TruthfulQA (0-shot)	59.35
Winogrande (5-shot)	77.90
GSM8k (5-shot)	52.31