Nexim-7b
Nexim-7b is a merge of the following models using mergekit:
🧩 Configuration
slices:
- sources:
- model: liminerity/m3
layer_range: [0, 32]
- model: liminerity/M7-7b
layer_range: [0, 32]
merge_method: slerp
base_model: liminerity/m3
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. | 76.53 |
| AI2 Reasoning Challenge (25-Shot) | 73.04 |
| HellaSwag (10-Shot) | 89.10 |
| MMLU (5-Shot) | 64.48 |
| TruthfulQA (0-shot) | 77.68 |
| Winogrande (5-shot) | 84.77 |
| GSM8k (5-shot) | 70.13 |
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Safetensors
Model size
7B params
Tensor type
BF16
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Model tree for gate369/Nexim-7b
Quantizations
1 modelEvaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard73.040
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard89.100
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.480
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard77.680
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard84.770
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard70.130