---
base_model:
- unsloth/Meta-Llama-3.1-8B
- unsloth/Meta-Llama-3.1-8B-Instruct
library_name: transformers
tags:
- mergekit
- merge
model-index:
- name: Meta-Llama-3.1-8B-Instruct-TIES
  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: 54.24
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/Meta-Llama-3.1-8B-Instruct-TIES
      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: 29.77
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/Meta-Llama-3.1-8B-Instruct-TIES
      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: 20.02
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/Meta-Llama-3.1-8B-Instruct-TIES
      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: 5.93
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/Meta-Llama-3.1-8B-Instruct-TIES
      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: 8.04
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/Meta-Llama-3.1-8B-Instruct-TIES
      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: 30.89
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/Meta-Llama-3.1-8B-Instruct-TIES
      name: Open LLM Leaderboard
---
# Rombo Llama Merge Test

This merge provides a baseline for performance when the instruct model is merged on the base.
It follows Rombodawg's merge method on Qwen models, and should prove if it works with Llama models.
Running hypothesis is that the IFEval benchmark will get nuked.
A success will be little to no performance change over the vanilla instruct model.

## Merge Details
### Merge Method

This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [unsloth/Meta-Llama-3.1-8B](https://huggingface.co/unsloth/Meta-Llama-3.1-8B) as a base.

### Models Merged

The following models were included in the merge:
* [unsloth/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: unsloth/Meta-Llama-3.1-8B
dtype: bfloat16
merge_method: ties
parameters:
  density: 1.0
  weight: 1.0
slices:
- sources:
  - layer_range: [0, 32]
    model: unsloth/Meta-Llama-3.1-8B-Instruct
    parameters:
      density: 1.0
      weight: 1.0
  - layer_range: [0, 32]
    model: unsloth/Meta-Llama-3.1-8B
tokenizer_source: unsloth/Meta-Llama-3.1-8B-Instruct
```

# [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__Meta-Llama-3.1-8B-Instruct-TIES-details)!
Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=T145/Meta-Llama-3.1-8B-Instruct-TIES)!

|      Metric       |% Value|
|-------------------|------:|
|Avg.               |  24.81|
|IFEval (0-Shot)    |  54.24|
|BBH (3-Shot)       |  29.77|
|MATH Lvl 5 (4-Shot)|  20.02|
|GPQA (0-shot)      |   5.93|
|MuSR (0-shot)      |   8.04|
|MMLU-PRO (5-shot)  |  30.89|