---
license: apache-2.0
library_name: transformers
tags:
- merge
- mergekit
- lazymergekit
base_model:
- vicgalle/Configurable-Llama-3.1-8B-Instruct
- cognitivecomputations/dolphin-2.9.4-llama3.1-8b
- NousResearch/Hermes-3-Llama-3.1-8B
- NeverSleep/Lumimaid-v0.2-8B
- Sao10K/L3-8B-Stheno-v3.2
- DreadPoor/ScaduTorrent-8B-model_stock
model-index:
- name: Trinas_Nectar-8B-model_stock
  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: 72.59
      name: strict accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=DreadPoor/Trinas_Nectar-8B-model_stock
      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: 31.98
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=DreadPoor/Trinas_Nectar-8B-model_stock
      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: 13.75
      name: exact match
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=DreadPoor/Trinas_Nectar-8B-model_stock
      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: 4.81
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=DreadPoor/Trinas_Nectar-8B-model_stock
      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: 11.41
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=DreadPoor/Trinas_Nectar-8B-model_stock
      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: 29.09
      name: accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=DreadPoor/Trinas_Nectar-8B-model_stock
      name: Open LLM Leaderboard
---

# Trinas_Nectar-8B-model_stock

This model hopes to be an improvement over [ONeil](https://huggingface.co./DreadPoor/ONeil-model_stock-8B)

Trinas_Nectar-8B-model_stock is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):

## 🧩 Configuration

```yaml
models: 
 - model: vicgalle/Configurable-Llama-3.1-8B-Instruct
 - model: cognitivecomputations/dolphin-2.9.4-llama3.1-8b
 - model: NousResearch/Hermes-3-Llama-3.1-8B
 - model: NeverSleep/Lumimaid-v0.2-8B
 - model: DreadPoor/ScaduTorrent-8B-model_stock
merge_method: model_stock
base_model: Sao10K/L3-8B-Stheno-v3.2 
normalize: false
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_DreadPoor__Trinas_Nectar-8B-model_stock)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |27.27|
|IFEval (0-Shot)    |72.59|
|BBH (3-Shot)       |31.98|
|MATH Lvl 5 (4-Shot)|13.75|
|GPQA (0-shot)      | 4.81|
|MuSR (0-shot)      |11.41|
|MMLU-PRO (5-shot)  |29.09|