README.md

---
language:
- en
license: cc-by-nc-4.0
library_name: transformers
tags:
- mergekit
- merge
base_model:
- SanjiWatsuki/Kunoichi-DPO-v2-7B
- macadeliccc/WestLake-7B-v2-laser-truthy-dpo
model-index:
- name: finch
  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: 71.59
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=antiven0m/finch
      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: 87.87
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=antiven0m/finch
      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: 64.81
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=antiven0m/finch
      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: 67.96
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=antiven0m/finch
      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: 84.14
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=antiven0m/finch
      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: 66.34
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=antiven0m/finch
      name: Open LLM Leaderboard
---

![Finch](https://i.imgur.com/Da14544.gif)

# **Finch 7b Merge**
## A SLERP merge of my two current fav 7B models

[macadeliccc/WestLake-7B-v2-laser-truthy-dpo](https://huggingface.co/macadeliccc/WestLake-7B-v2-laser-truthy-dpo) & [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-DPO-v2-7B)

- [6bpw EXL2 Quant](https://huggingface.co/antiven0m/finch-6bpw-exl2)
- [GGUF Quants](https://huggingface.co/antiven0m/finch-gguf)

## Settings
I reccomend using the **ChatML** format. As for samplers, I reccomend the following:
```yml
Temperature: 1.2
Min P: 0.2
Smoothing Factor: 0.2
```
## Mergekit Config
```yaml
base_model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
dtype: float16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.5, 0.3, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.5, 0.7, 0.3, 0.0]
  - value: 0.5
slices:
- sources:
  - layer_range: [0, 32]
    model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
  - layer_range: [0, 32]
    model: SanjiWatsuki/Kunoichi-DPO-v2-7B
```
# [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_antiven0m__finch)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |73.78|
|AI2 Reasoning Challenge (25-Shot)|71.59|
|HellaSwag (10-Shot)              |87.87|
|MMLU (5-Shot)                    |64.81|
|TruthfulQA (0-shot)              |67.96|
|Winogrande (5-shot)              |84.14|
|GSM8k (5-shot)                   |66.34|