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---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- Locutusque/Llama-3-NeuralHercules-5.0-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Hermes-2-Theta-Llama-3-8B
- Locutusque/llama-3-neural-chat-v2.2-8b
model-index:
- name: Llama-3-Yggdrasil-2.0-8B
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: 53.71
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/Llama-3-Yggdrasil-2.0-8B
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: 26.92
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/Llama-3-Yggdrasil-2.0-8B
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: 6.87
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/Llama-3-Yggdrasil-2.0-8B
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: 1.68
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/Llama-3-Yggdrasil-2.0-8B
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: 8.07
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/Llama-3-Yggdrasil-2.0-8B
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: 24.07
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/Llama-3-Yggdrasil-2.0-8B
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 [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) as a base.
### Models Merged
The following models were included in the merge:
* [Locutusque/Llama-3-NeuralHercules-5.0-8B](https://huggingface.co/Locutusque/Llama-3-NeuralHercules-5.0-8B)
* [NousResearch/Hermes-2-Theta-Llama-3-8B](https://huggingface.co/NousResearch/Hermes-2-Theta-Llama-3-8B)
* [Locutusque/llama-3-neural-chat-v2.2-8b](https://huggingface.co/Locutusque/llama-3-neural-chat-v2.2-8b)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
- model: NousResearch/Meta-Llama-3-8B
# No parameters necessary for base model
- model: NousResearch/Hermes-2-Theta-Llama-3-8B
parameters:
density: 0.6
weight: 0.55
- model: Locutusque/llama-3-neural-chat-v2.2-8b
parameters:
density: 0.55
weight: 0.4
- model: Locutusque/Llama-3-NeuralHercules-5.0-8B
parameters:
density: 0.65
weight: 0.6
merge_method: dare_ties
base_model: NousResearch/Meta-Llama-3-8B
parameters:
int8_mask: true
dtype: bfloat16
```
# [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/details_Locutusque__Llama-3-Yggdrasil-2.0-8B)
| Metric |Value|
|-------------------|----:|
|Avg. |20.22|
|IFEval (0-Shot) |53.71|
|BBH (3-Shot) |26.92|
|MATH Lvl 5 (4-Shot)| 6.87|
|GPQA (0-shot) | 1.68|
|MuSR (0-shot) | 8.07|
|MMLU-PRO (5-shot) |24.07|
|