Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
GGUF from mradermacher!
GGUF from QuantFactory!
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the SLERP merge method. (sophosympatheia gradient)
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: Qwen/Qwen2.5-14B-Instruct
merge_method: slerp
base_model: v000000/Qwen2.5-14B-Gutenberg-1e-Delta
parameters:
t:
- value: [0, 0, 0.3, 0.4, 0.5, 0.6, 0.5, 0.4, 0.3, 0, 0]
dtype: bfloat16
The idea here is that Gutenberg DPO stays in the output/input 100% while merging smoothly with the base instruct model in the deeper layers to heal loss and increase intelligence.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 33.39 |
| IFEval (0-Shot) | 48.55 |
| BBH (3-Shot) | 49.74 |
| MATH Lvl 5 (4-Shot) | 19.71 |
| GPQA (0-shot) | 15.21 |
| MuSR (0-shot) | 18.43 |
| MMLU-PRO (5-shot) | 48.68 |
- Downloads last month
- 2,519
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
Merge model
this model
Dataset used to train v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard48.550
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard49.740
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard19.710
- acc_norm on GPQA (0-shot)Open LLM Leaderboard15.210
- acc_norm on MuSR (0-shot)Open LLM Leaderboard18.430
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard48.680