README.md

---
license: cc-by-nc-4.0
library_name: transformers
tags:
- llama-3
model-index:
- name: badger-l3-instruct-32k
  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: 63.65
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/badger-l3-instruct-32k
      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: 81.4
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/badger-l3-instruct-32k
      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: 67.13
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/badger-l3-instruct-32k
      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: 55.02
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/badger-l3-instruct-32k
      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: 77.35
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/badger-l3-instruct-32k
      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: 72.4
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/badger-l3-instruct-32k
      name: Open LLM Leaderboard
---

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65b19c1b098c85365af5a83e/5dq0evzBjVulEOjYHW68O.png)

*updated with fixed tokenizer config*

# Badger/δ Llama 3 Instruct 32k

I haven't been releasing my base merges so far, but this one seems worthy.

Badger is a *recursive maximally disjoint pairwise normalized fourier interpolation* of the following models:

```python
models = [
 'Einstein-v6.1-Llama3-8B',
 'L3-TheSpice-8b-v0.8.3',
 'dolphin-2.9-llama3-8b',
 'Configurable-Hermes-2-Pro-Llama-3-8B',
 'MAmmoTH2-8B-Plus',
 'Pantheon-RP-1.0-8b-Llama-3',
 'Tiamat-8b-1.2-Llama-3-DPO',
 'Buzz-8b-Large-v0.5',
 'Kei_Llama3_8B',
 'Llama-3-Lumimaid-8B-v0.1',
 'llama-3-cat-8b-instruct-pytorch',
 'Llama-3SOME-8B-v1',
 'Roleplay-Llama-3-8B',
 'Llama-3-LewdPlay-8B-evo',
 'opus-v1.2-llama-3-8b-instruct-run3.5-epoch2.5',
 'meta-llama-3-8b-instruct-hf-ortho-baukit-5fail-3000total-bf16',
 'Poppy_Porpoise-0.72-L3-8B',
 'Llama-3-8B-Instruct-norefusal',
 'Meta-Llama-3-8B-Instruct-DPO',
 'badger',
 'Llama-3-Refueled',
 'Llama-3-8B-Instruct-DPO-v0.4',
 'Llama-3-8B-Instruct-Gradient-1048k',
 'Mahou-1.0-llama3-8B',
 'Llama-3-SauerkrautLM-8b-Instruct',
 'Llama-3-Soliloquy-8B-v2'
]
```

I have included the notebook code I used to generate the model, for any that are curious.  I have adjusted the config for rope scale 4, and 16k-32k context both seem coherent.

# [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_maldv__badger-l3-instruct-32k)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |69.49|
|AI2 Reasoning Challenge (25-Shot)|63.65|
|HellaSwag (10-Shot)              |81.40|
|MMLU (5-Shot)                    |67.13|
|TruthfulQA (0-shot)              |55.02|
|Winogrande (5-shot)              |77.35|
|GSM8k (5-shot)                   |72.40|