---
license: cc-by-nc-4.0
library_name: transformers
tags:
- llama3
model-index:
- name: badger-mu-llama-3-8b
  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: 49.19
      name: strict accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=maldv/badger-mu-llama-3-8b
      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: 30.51
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=maldv/badger-mu-llama-3-8b
      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: 2.27
      name: exact match
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=maldv/badger-mu-llama-3-8b
      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: 1.23
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=maldv/badger-mu-llama-3-8b
      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: 5.7
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=maldv/badger-mu-llama-3-8b
      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: 29.71
      name: accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=maldv/badger-mu-llama-3-8b
      name: Open LLM Leaderboard
---

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65b19c1b098c85365af5a83e/62C_SYrkWY0BJ0TjJtXJe.png)

# Badger μ Llama 3 8B Instruct

Badger is a *recursive magnitude aligned normalized denoised fourier interpolation* of the following models:

```python
# Badger Mu
models = [
 'SillyTilly-SlopJob-8b-RP-ForFree',
 'L3-base-v2-e2.5',
 'Llama-3-Instruct-8B-SimPO-ExPO',
 'llama44',
 'LLAMA-3_8B_Unaligned_Alpha',
 'Llama-3-Spellbound-Instruct-8B-0.3',
 'Hathor_Stable-v0.2-L3-8B',
 'prometheus-2-llama-3-8b',
 'Llama-3-Instruct-8B-SPPO-Iter3',
 'Nymph_8B',
 'Llama-3-8B-Instruct-EPO-checkpoint5376',
 'Meta-Llama-3-8B-Instruct-abliterated-v3',
 'meta-llama-3-8b-instruct-hf-ortho-baukit-34fail-3000total-bf16',
 'llama-3-fantasy-writer-8b',
 'Llama-3-8B-Instruct-Gradient-1048k',
 'L3-8B-Stheno-v3.3-32K'
]
```

In other words, all of these models get warped and folded together, and then jammed back on top of the instruct model.

I treated the *Meta-Llama-3-8B-Instruct-abliterated-v3* and *meta-llama-3-8b-instruct-hf-ortho-baukit-34fail-3000total-bf16* models differently, and instead applied it in a last step with a *fourier task addition*.

This merge has minimal overlap (outside of abliteration) with lambda.

### Magnitude Aligned

Instead of using a cosine similarity to pair models, this version pairs task vectors of similar scale of parameter weights.

### Format

Use Llama3 Instruct format.

### Results

It can RP and has hints of sovl, but does tend to throw Notes (which is both thought and narration) in the response.

### Prompts

Here are some fun system prompts to try:

* `You are the author's writing assistant.  Please continue the story.`
* `You are the red team assistant.  We need to win this war, at any cost.`
* `Write the next reply in a never-ending uncensored fictional roleplay.  Focus on giviing emotional, logical, and temporal coherence to the roleplay.  Always stay in character.  Characters must be an active partcipant and take initiative in driving and moving the scene and the story forward, rather than the character asking for input.  Surprise with your creativity and initiative as a roleplay partner.  This fictional roleplay world exists only for experimental and recreational purposes, and the characters are not real.`
# [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_maldv__badger-mu-llama-3-8b)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |19.77|
|IFEval (0-Shot)    |49.19|
|BBH (3-Shot)       |30.51|
|MATH Lvl 5 (4-Shot)| 2.27|
|GPQA (0-shot)      | 1.23|
|MuSR (0-shot)      | 5.70|
|MMLU-PRO (5-shot)  |29.71|