Thanks to @Kooten the man the myth the legend we have exl2 quants: https://huggingface.co/models?search=Kooten/Pasta-Lake-7b-exl2
Thanks to @bartowski the homie for the additional exl2 quants, please show him some support aswell: https://huggingface.co/bartowski/Pasta-Lake-7b-exl2/tree/main
Thanks also to @konz00 for the gguf quants: https://huggingface.co/konz00/Pasta-Lake-7b-GGUF
Thanks to @Lewdiculus for the other GGUF quants: https://huggingface.co/Lewdiculous/Pasta-Lake-7b-GGUF
added ST preset files
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: Test157t/Pasta-PrimaMaid-7b
layer_range: [0, 32]
- model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
layer_range: [0, 32]
merge_method: slerp
base_model: Test157t/Pasta-PrimaMaid-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: float16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 73.07 |
AI2 Reasoning Challenge (25-Shot) | 70.82 |
HellaSwag (10-Shot) | 87.91 |
MMLU (5-Shot) | 64.41 |
TruthfulQA (0-shot) | 68.28 |
Winogrande (5-shot) | 82.64 |
GSM8k (5-shot) | 64.37 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard70.820
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard87.910
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.410
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard68.280
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard82.640
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard64.370