Mistral 7B Merges
Collection
Merges that may or may not be worth using. All credit goes to Maxime Labonne's course, https://github.com/mlabonne/llm-course, + mergekit
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6 items
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Updated
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1
RandomMergeNoNormWEIGHTED-7B-DARETIES is a merge of the following models using mergekit:
models:
- model: FelixChao/WestSeverus-7B-DPO-v2
# No parameters necessary for base model
- model: FelixChao/WestSeverus-7B-DPO-v2
parameters:
density: [1, 0.7, 0.1]
weight: [0, 0.3, 0.7, 1]
- model: CultriX/Wernicke-7B-v9
parameters:
density: [1, 0.7, 0.3]
weight: [0, 0.25, 0.5, 1]
- model: mlabonne/NeuralBeagle14-7B
parameters:
density: 0.25
weight:
- filter: mlp
value: 0.5
- value: 0
merge_method: ties
base_model: FelixChao/WestSeverus-7B-DPO-v2
parameters:
int8_mask: true
normalize: true
sparsify:
- filter: mlp
value: 0.5
- filter: self_attn
value: 0.5
dtype: float16
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 75.36 |
AI2 Reasoning Challenge (25-Shot) | 73.38 |
HellaSwag (10-Shot) | 88.50 |
MMLU (5-Shot) | 64.94 |
TruthfulQA (0-shot) | 71.50 |
Winogrande (5-shot) | 83.58 |
GSM8k (5-shot) | 70.28 |