--- language: - en tags: - text2text-generation - mistral - roleplay - merge - summarization - not-for-all-audiences - nsfw 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 --- # Most uncensored and obscene open neural network in the world (2024) `The comeback of Uncensored AI Dungeon Griffin 2020 LET'S FUCKING GOOOOOOOO!!!!!!` If this model seems too old and dumb to you (and/or you do not want English): I recommend use `UnslopNemo-12B-v4.1`. I do not know anything more Uncensored and New model. But it is absolutely not a fact that it is more uncensored as mine. YOU CAN talk about: Rape, 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. The "censorbench" by jts2323 example # [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|