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---
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 mased on Mistral v0.01 with a 8192 Context length that likes to chat, roleplay, work with agents, do some light 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
```
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