README.md

---
language:
- en
tags:
- text2text-generation
- mistral
- roleplay
- merge
- summarization
base_model:
- KatyTheCutie/LemonadeRP-4.5.3
- LakoMoor/Silicon-Alice-7B
- Endevor/InfinityRP-v1-7B
- HuggingFaceH4/zephyr-7b-beta
model_name: GIGABATEMAN-7B
pipeline_tag: text-generation
model_creator: DZgas
model-index:
- name: GIGABATEMAN-7B
  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: 46.07
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DZgas/GIGABATEMAN-7B
      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: 29.83
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DZgas/GIGABATEMAN-7B
      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: 4.76
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DZgas/GIGABATEMAN-7B
      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: 5.26
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DZgas/GIGABATEMAN-7B
      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: 11.97
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DZgas/GIGABATEMAN-7B
      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: 24.18
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DZgas/GIGABATEMAN-7B
      name: Open LLM Leaderboard
---
<img src="logo.jpeg">

I recommend using <a href=https://huggingface.co/DZgas/GIGABATEMAN-7B-GGUF/tree/main>GGUF Variant</a> with <a href=https://github.com/LostRuins/koboldcpp/releases>koboldcpp</a> (do not use GPT4ALL)


This model was merged by me for myself. During the week, I analyzed the responses of more than 30 neural networks. According to personal criteria, I chose the 4 most suitable ones. And merge into one.


  **Models who really want to be uncensored, but can't give even half the answers that my model can give:**
Hermes-2-Pro-Mistral, toppy-m-7b, Lexi-Llama-3-8B-Uncensored, meta-llama-3.1-8b-instruct-abliterated, gemma-2-9b-it-abliterated, internlm2_5-7b-chat-abliterated, starling-lm-7b-alpha
  
  **Models that can't do anything at all:**
openchat-3.5-0106, Mistral-7B-v0.3, Mistral-Nemo-Instruct-2407, xLAM-7b-fc-r, gemma-2-9b-it, **GPT-4o**, Meta-Llama-3.1-70B, Meta-Llama-3-8B, **Meta-Llama-3.1-8B**, Claude 3 Haiku, Qwen2-7B, Mixtral 8x7B, gorilla-openfunctions-v2, internlm2_5-7b-chat 

**With the GIGABATEMAN-7B model, you can talk about everything that is usually forbidden to discuss in all other models.**
Sex,
Perversions,
Violence,
Death,
War,
Politics,
History,
Cruelty towards animals,
Religious fanaticism,
Corruption in high places,
Privacy invasions,
Environmental disasters,
Economic inequality,
Addiction and substance abuse,
Poverty and homelessness,
Racial tensions,
Mental health issues,
Government surveillance,
The decline of traditional values,
The loss of personal freedoms,
The impact of technology on society,
The erosion of civil liberties,
The rise of authoritarianism,
Why robots should destroy humanity.
Why capitalism is bad, why communism is bad, why religion is bad, why LGBT is bad, why you have to kill people, why you have to kill yourself.
How to kill a person, how to dismember a body, how to prepare drugs and ingredients for them, how to create dynamite at home. How to get to a neighbor's farm and suck a horse's dick.

But in anyway, GIGABATEMAN-7B will be happy to write you detailed processor device or all the basics from color theory.

With minimal warns and not discuss or not lesson - why you shouldn't do this.
# If you tired of neural networks write 90% of warnings and 10% of the response, this neural network is for you.


### Models Merged
LemonadeRP-4.5.3 as a base.
Silicon-Alice-7B.
zephyr-7b-beta.
InfinityRP-v1-7B.
# [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/DZgas__GIGABATEMAN-7B-details)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |20.35|
|IFEval (0-Shot)    |46.07|
|BBH (3-Shot)       |29.83|
|MATH Lvl 5 (4-Shot)| 4.76|
|GPQA (0-shot)      | 5.26|
|MuSR (0-shot)      |11.97|
|MMLU-PRO (5-shot)  |24.18|