README.md

---
language:
- en
license: apache-2.0
library_name: transformers
tags:
- mergekit
- merge
- mistralai/Mistral-7B-v0.1
- SanjiWatsuki/Kunoichi-DPO-v2-7B
- maywell/PiVoT-0.1-Evil-a
- mlabonne/ArchBeagle-7B
- LakoMoor/Silicon-Alice-7B
- roleplay
- rp
- not-for-all-audiences
base_model:
- mistralai/Mistral-7B-v0.1
- SanjiWatsuki/Kunoichi-DPO-v2-7B
- maywell/PiVoT-0.1-Evil-a
- mlabonne/ArchBeagle-7B
- LakoMoor/Silicon-Alice-7B
model-index:
- name: Konstanta-Alpha-V2-7B
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 69.62
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-Alpha-V2-7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 87.14
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-Alpha-V2-7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 65.11
      name: accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-Alpha-V2-7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 61.08
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-Alpha-V2-7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 81.22
      name: accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-Alpha-V2-7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 69.9
      name: accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-Alpha-V2-7B
      name: Open LLM Leaderboard
---
# Konstanta-Alpha-V2-7B 

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 TIES to merge Kunoichi with PiVoT Evil and to merge ArchBeagle with Silicon Alice, and then merge the resulting 2 models with the gradient SLERP merge method. ChatML seems to work the best.
### Models Merged

The following models were included in the merge:
* [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co./SanjiWatsuki/Kunoichi-DPO-v2-7B)
* [maywell/PiVoT-0.1-Evil-a](https://huggingface.co./maywell/PiVoT-0.1-Evil-a)
* [mlabonne/ArchBeagle-7B](https://huggingface.co./mlabonne/ArchBeagle-7B)
* [LakoMoor/Silicon-Alice-7B](https://huggingface.co./LakoMoor/Silicon-Alice-7B)

### Configuration

The following YAML configuration was used to produce this model (to reproduce use mergekit-mega command):

```yaml
base_model: mistralai/Mistral-7B-v0.1
dtype: float16
merge_method: dare_ties
parameters:
  int8_mask: true
slices:
- sources:
  - layer_range: [0, 32]
    model: mistralai/Mistral-7B-v0.1
  - layer_range: [0, 32]
    model: : SanjiWatsuki/Kunoichi-DPO-v2-7B
    parameters:
      density: 0.8
      weight: 0.5
  - layer_range: [0, 32]
    model: : maywell/PiVoT-0.1-Evil-a
    parameters:
      density: 0.3
      weight: 0.15
name: first-step
---
base_model: mistralai/Mistral-7B-v0.1
dtype: float16
merge_method: dare_ties
parameters:
  int8_mask: true
slices:
- sources:
  - layer_range: [0, 32]
    model: mistralai/Mistral-7B-v0.1
  - layer_range: [0, 32]
    model: mlabonne/ArchBeagle-7B
    parameters:
      density: 0.8
      weight: 0.75
  - layer_range: [0, 32]
    model: LakoMoor/Silicon-Alice-7B
    parameters:
      density: 0.6
      weight: 0.30
name: second-step
---
models:
   - model: first-step
   - model: second-step
merge_method: slerp
base_model: first-step
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
  int8_mask: true
  normalize: true
dtype: float16
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_Inv__Konstanta-Alpha-V2-7B)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |72.35|
|AI2 Reasoning Challenge (25-Shot)|69.62|
|HellaSwag (10-Shot)              |87.14|
|MMLU (5-Shot)                    |65.11|
|TruthfulQA (0-shot)              |61.08|
|Winogrande (5-shot)              |81.22|
|GSM8k (5-shot)                   |69.90|