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:
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 |