haLLawa4-7b
haLLawa4-7b is a merge of the following models using mergekit:
🧩 Configuration
```yaml models:
- model: eren23/ogno-monarch-jaskier-merge-7b
No parameters necessary for base model
- model: mlabonne/Monarch-7B #Emphasize the beginning of Vicuna format models parameters: weight: 0.5 density: 0.59
- model: paulml/OGNO-7B parameters: weight: 0.2 density: 0.55
Vicuna format
- model: AbacusResearch/haLLAwa3 parameters: weight: 0.3 density: 0.55
merge_method: dare_ties base_model: eren23/ogno-monarch-jaskier-merge-7b parameters: int8_mask: true dtype: bfloat16 random_seed: 0 ```
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 75.25 |
AI2 Reasoning Challenge (25-Shot) | 71.50 |
HellaSwag (10-Shot) | 88.36 |
MMLU (5-Shot) | 64.49 |
TruthfulQA (0-shot) | 74.27 |
Winogrande (5-shot) | 82.40 |
GSM8k (5-shot) | 70.51 |
- Downloads last month
- 60
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for AbacusResearch/haLLawa4-7b
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard71.500
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard88.360
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.490
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard74.270
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard82.400
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard70.510