Gonzo-Chat-7B/README.md

---
language:
- en
license: apache-2.0
library_name: transformers
tags:
- mergekit
- merge
base_model:
- Nondzu/Mistral-7B-Instruct-v0.2-code-ft
- NousResearch/Nous-Hermes-2-Mistral-7B-DPO
- cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
- eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO
model-index:
- name: Gonzo-Chat-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: 65.02
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Chat-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: 85.4
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Chat-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: 63.75
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Chat-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: 60.23
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Chat-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: 77.74
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Chat-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: 47.61
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Chat-7B
      name: Open LLM Leaderboard
---
# Gonzo-Chat-7B

Gonzo-Chat-7B is a merged LLM based on Mistral v0.01 with a 8192 Context length that likes to chat, roleplay, work with agents, do some lite programming, and then beat the brakes off you in the back alley...

The ***BEST*** Open Source 7B **Street Fighting** LLM of 2024!!!

![SF-III.jpg](https://cdn-uploads.huggingface.co/production/uploads/635bf4cfca038892de049862/txhGhwRWWbZAuKQET-v8F.jpeg)


# [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_Badgids__Gonzo-Chat-7B)

| Metric                            | Value |
| --------------------------------- | ----: |
| Avg.                              | 66.63 |
| AI2 Reasoning Challenge (25-Shot) | 65.02 |
| HellaSwag (10-Shot)               | 85.40 |
| MMLU (5-Shot)                     | 63.75 |
| TruthfulQA (0-shot)               | 60.23 |
| Winogrande (5-shot)               | 77.74 |
| GSM8k (5-shot)                    | 47.61 |



## LLM-Colosseum Results


All contestents fought using the same LLM-Colosseum default settings. Each contestant fought 25 rounds with every other contestant.

https://github.com/OpenGenerativeAI/llm-colosseum



### Gonzo-Chat-7B .vs Mistral v0.2, Dolphon-Mistral v0.2, Deepseek-Coder-6.7b-instruct


![games-won.png](https://cdn-uploads.huggingface.co/production/uploads/635bf4cfca038892de049862/gZHRuz7KO6-czOEcPwZw_.png)

![download.png](https://cdn-uploads.huggingface.co/production/uploads/635bf4cfca038892de049862/UubKr4WlnWjnmt8Eh9xkk.png)


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](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO](https://huggingface.co/eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO) as a base.

### Models Merged

The following models were included in the merge:
* [Nondzu/Mistral-7B-Instruct-v0.2-code-ft](https://huggingface.co/Nondzu/Mistral-7B-Instruct-v0.2-code-ft)
* [NousResearch/Nous-Hermes-2-Mistral-7B-DPO](https://huggingface.co/NousResearch/Nous-Hermes-2-Mistral-7B-DPO)
* [cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser](https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO
    # No parameters necessary for base model
  - model: cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
    parameters:
      density: 0.53
      weight: 0.4
  - model:  NousResearch/Nous-Hermes-2-Mistral-7B-DPO
    parameters:
      density: 0.53
      weight: 0.3
  - model: Nondzu/Mistral-7B-Instruct-v0.2-code-ft
    parameters:
      density: 0.53
      weight: 0.3
merge_method: dare_ties
base_model: eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO
parameters:
  int8_mask: true
dtype: bfloat16
```