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---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- akjindal53244/Llama-3.1-Storm-8B
- Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
- arcee-ai/Llama-3.1-SuperNova-Lite
- unsloth/Meta-Llama-3.1-8B-Instruct
model-index:
- name: ZEUS-8B-V10
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: wis-k/instruction-following-eval
split: train
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 77.07
name: averaged accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V10
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: SaylorTwift/bbh
split: test
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 32.7
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V10
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: lighteval/MATH-Hard
split: test
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 20.09
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V10
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
split: train
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 9.96
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V10
name: Open LLM Leaderboard
new_version: T145/ZEUS-8B-V13
---
# ZEUS 8B 🌩️ V10
A V2 recreation with a few changes:
* Unified tokenizer (no noticeable changes)
* Using `int_mask` and `normalize` (the latter being enabled by default in mergekit)
* Using a preset seed to create a reproducible config (due to DARE relying on RNG)
Expecting little to no change over V2.
## Merge Details
### Merge Method
This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [unsloth/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct) as a base.
### Models Merged
The following models were included in the merge:
* [akjindal53244/Llama-3.1-Storm-8B](https://huggingface.co/akjindal53244/Llama-3.1-Storm-8B)
* [Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2](https://huggingface.co/Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2)
* [arcee-ai/Llama-3.1-SuperNova-Lite](https://huggingface.co/arcee-ai/Llama-3.1-SuperNova-Lite)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
base_model: unsloth/Meta-Llama-3.1-8B-Instruct
dtype: bfloat16
merge_method: dare_ties
parameters:
int8_mask: 1.0
normalize: 1.0
random_seed: 42.0
slices:
- sources:
- layer_range: [0, 32]
model: akjindal53244/Llama-3.1-Storm-8B
parameters:
density: 0.8
weight: 0.25
- layer_range: [0, 32]
model: arcee-ai/Llama-3.1-SuperNova-Lite
parameters:
density: 0.8
weight: 0.33
- layer_range: [0, 32]
model: Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
parameters:
density: 0.8
weight: 0.42
- layer_range: [0, 32]
model: unsloth/Meta-Llama-3.1-8B-Instruct
tokenizer_source: union
```
# [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/T145__ZEUS-8B-V10-details)!
Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=T145/ZEUS-8B-V10)!
| Metric |Value (%)|
|-------------------|--------:|
|**Average** | 30.19|
|IFEval (0-Shot) | 77.07|
|BBH (3-Shot) | 32.70|
|MATH Lvl 5 (4-Shot)| 20.09|
|GPQA (0-shot) | 9.96|
|MuSR (0-shot) | 9.09|
|MMLU-PRO (5-shot) | 32.26|
## Changes over V2
| Metric |Change|
|-------------------|-----:|
|Avg. |+0.12|
|IFEval (0-Shot) |-3.22|
|BBH (3-Shot) |+1.09|
|MATH Lvl 5 (4-Shot)|-1.06|
|GPQA (0-shot) |+3.02|
|MuSR (0-shot) |+0.85|
|MMLU-PRO (5-shot) |+0.08| |