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---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
- EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2
- v000000/Qwen2.5-Lumen-14B
- qwen/Qwen2.5-14b
- arcee-ai/SuperNova-Medius
- allura-org/TQ2.5-14B-Aletheia-v1
model-index:
- name: Q2.5-Veltha-14B
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 82.92
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/Q2.5-Veltha-14B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 49.75
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/Q2.5-Veltha-14B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 28.02
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/Q2.5-Veltha-14B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 14.54
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/Q2.5-Veltha-14B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 12.26
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/Q2.5-Veltha-14B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 47.76
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/Q2.5-Veltha-14B
name: Open LLM Leaderboard
---
# merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the della_linear merge method using [qwen/Qwen2.5-14b](https://huggingface.co/qwen/Qwen2.5-14b) as a base.
### Models Merged
The following models were included in the merge:
* [huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2](https://huggingface.co/huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2)
* [EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2)
* [v000000/Qwen2.5-Lumen-14B](https://huggingface.co/v000000/Qwen2.5-Lumen-14B)
* [arcee-ai/SuperNova-Medius](https://huggingface.co/arcee-ai/SuperNova-Medius)
* [allura-org/TQ2.5-14B-Aletheia-v1](https://huggingface.co/allura-org/TQ2.5-14B-Aletheia-v1)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
merge_method: della_linear
dtype: float32
out_dtype: bfloat16
parameters:
epsilon: 0.04
lambda: 1.05
normalize: true
base_model: qwen/Qwen2.5-14b
tokenizer_source: arcee-ai/SuperNova-Medius
models:
- model: arcee-ai/SuperNova-Medius
parameters:
weight: 10
density: 1
- model: EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2
parameters:
weight: 7
density: 0.5
- model: v000000/Qwen2.5-Lumen-14B
parameters:
weight: 7
density: 0.4
- model: allura-org/TQ2.5-14B-Aletheia-v1
parameters:
weight: 8
density: 0.4
- model: huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
parameters:
weight: 8
density: 0.45
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/djuna__Q2.5-Veltha-14B-details)
| Metric |Value|
|-------------------|----:|
|Avg. |39.21|
|IFEval (0-Shot) |82.92|
|BBH (3-Shot) |49.75|
|MATH Lvl 5 (4-Shot)|28.02|
|GPQA (0-shot) |14.54|
|MuSR (0-shot) |12.26|
|MMLU-PRO (5-shot) |47.76|
|