README.md

---
license: other
tags:
- merge
- mergekit
- lazymergekit
base_model: mlabonne/Daredevil-8B
model-index:
- name: Daredevil-8B
  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: 68.86
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B
      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: 84.5
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B
      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: 69.24
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B
      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: 59.89
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B
      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: 78.45
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B
      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: 73.54
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B
      name: Open LLM Leaderboard
---

# Daredevil-8B-GGUF
This is quantized version of [mlabonne/Daredevil-8B](https://huggingface.co/mlabonne/Daredevil-8B) created using llama.cpp
## Model Description

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/gFEhcIDSKa3AWpkNfH91q.jpeg)

Daredevil-8B is a mega-merge designed to maximize MMLU. On 27 May 24, it is the Llama 3 8B model with the **highest MMLU score**.
From my experience, a high MMLU score is all you need with Llama 3 models.

It is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [nbeerbower/llama-3-stella-8B](https://huggingface.co/nbeerbower/llama-3-stella-8B)
* [Hastagaras/llama-3-8b-okay](https://huggingface.co/Hastagaras/llama-3-8b-okay)
* [nbeerbower/llama-3-gutenberg-8B](https://huggingface.co/nbeerbower/llama-3-gutenberg-8B)
* [openchat/openchat-3.6-8b-20240522](https://huggingface.co/openchat/openchat-3.6-8b-20240522)
* [Kukedlc/NeuralLLaMa-3-8b-DT-v0.1](https://huggingface.co/Kukedlc/NeuralLLaMa-3-8b-DT-v0.1)
* [cstr/llama3-8b-spaetzle-v20](https://huggingface.co/cstr/llama3-8b-spaetzle-v20)
* [mlabonne/ChimeraLlama-3-8B-v3](https://huggingface.co/mlabonne/ChimeraLlama-3-8B-v3)
* [flammenai/Mahou-1.1-llama3-8B](https://huggingface.co/flammenai/Mahou-1.1-llama3-8B)
* [KingNish/KingNish-Llama3-8b](https://huggingface.co/KingNish/KingNish-Llama3-8b)

Thanks to nbeerbower, Hastagaras, openchat, Kukedlc, cstr, flammenai, and KingNish for their merges. Special thanks to Charles Goddard and Arcee.ai for MergeKit.

## 🔎 Applications

You can use it as an improved version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct).

This is a censored model. For an uncensored version, see [mlabonne/Daredevil-8B-abliterated](https://huggingface.co/mlabonne/Daredevil-8B-abliterated).

Tested on LM Studio using the "Llama 3" preset.


## 🏆 Evaluation

### Open LLM Leaderboard

Daredevil-8B is the best-performing 8B model on the Open LLM Leaderboard in terms of MMLU score (27 May 24).

![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/xFKhGdSaIxL9_tcJPhM5w.png)

### Nous

Daredevil-8B is the best-performing 8B model on Nous' benchmark suite (evaluation performed using [LLM AutoEval](https://github.com/mlabonne/llm-autoeval), 27 May 24). See the entire leaderboard [here](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard).

| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
|---|---:|---:|---:|---:|---:|
| [**mlabonne/Daredevil-8B**](https://huggingface.co/mlabonne/Daredevil-8B) [📄](https://gist.github.com/mlabonne/080f9c5f153ea57a7ab7d932cf896f21) | **55.87** | **44.13** | **73.52** | **59.05** | **46.77** |
| [mlabonne/Daredevil-8B-abliterated](https://huggingface.co/mlabonne/Daredevil-8B-abliterated) [📄](https://gist.github.com/mlabonne/32cdd8460804662c856bcb2a20acd49e) | 55.06 | 43.29 | 73.33 | 57.47 | 46.17 |
| [mlabonne/Llama-3-8B-Instruct-abliterated-dpomix](https://huggingface.co/mlabonne/Llama-3-8B-Instruct-abliterated-dpomix) [📄](https://gist.github.com/mlabonne/d711548df70e2c04771cc68ab33fe2b9) | 52.26 | 41.6 | 69.95 | 54.22 | 43.26 |
| [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) [📄](https://gist.github.com/mlabonne/8329284d86035e6019edb11eb0933628) | 51.34 | 41.22 | 69.86 | 51.65 | 42.64 |
| [failspy/Meta-Llama-3-8B-Instruct-abliterated-v3](https://huggingface.co/failspy/Meta-Llama-3-8B-Instruct-abliterated-v3) [📄](https://gist.github.com/mlabonne/f46cce0262443365e4cce2b6fa7507fc) | 51.21 | 40.23 | 69.5 | 52.44 | 42.69 |
| [mlabonne/OrpoLlama-3-8B](https://huggingface.co/mlabonne/OrpoLlama-3-8B) [📄](https://gist.github.com/mlabonne/22896a1ae164859931cc8f4858c97f6f) | 48.63 | 34.17 | 70.59 | 52.39 | 37.36 |
| [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) [📄](https://gist.github.com/mlabonne/616b6245137a9cfc4ea80e4c6e55d847) | 45.42 | 31.1 | 69.95 | 43.91 | 36.7 |

## 🌳 Model family tree

![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/ekwRGgnjzEOyprT8sEBFt.png)

## 🧩 Configuration

```yaml
models:
  - model: NousResearch/Meta-Llama-3-8B
    # No parameters necessary for base model
  - model: nbeerbower/llama-3-stella-8B
    parameters:
      density: 0.6
      weight: 0.16
  - model: Hastagaras/llama-3-8b-okay
    parameters:
      density: 0.56
      weight: 0.1
  - model: nbeerbower/llama-3-gutenberg-8B
    parameters:
      density: 0.6
      weight: 0.18
  - model: openchat/openchat-3.6-8b-20240522
    parameters:
      density: 0.56
      weight: 0.12
  - model: Kukedlc/NeuralLLaMa-3-8b-DT-v0.1
    parameters:
      density: 0.58
      weight: 0.18
  - model: cstr/llama3-8b-spaetzle-v20
    parameters:
      density: 0.56
      weight: 0.08
  - model: mlabonne/ChimeraLlama-3-8B-v3
    parameters:
      density: 0.56
      weight: 0.08
  - model: flammenai/Mahou-1.1-llama3-8B
    parameters:
      density: 0.55
      weight: 0.05
  - model: KingNish/KingNish-Llama3-8b
    parameters:
      density: 0.55
      weight: 0.05
merge_method: dare_ties
base_model: NousResearch/Meta-Llama-3-8B
dtype: bfloat16
```