--- language: - en - fr - es - ru - zh - ja - fa - code license: mit library_name: transformers base_model: - fluently-lm/FluentlyLM-Prinum tags: - abliterated - uncensored - fluently-lm - fluently - prinum - instruct - trained - math - roleplay - reasoning - axolotl - unsloth - argilla - qwen2 datasets: - fluently-sets/ultraset - fluently-sets/ultrathink - fluently-sets/reasoning-1-1k - fluently-sets/MATH-500-Overall inference: true pipeline_tag: text-generation model-index: - name: FluentlyLM-Prinum 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: 80.9 name: strict accuracy source: url: >- https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fluently-lm/FluentlyLM-Prinum 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: 59.48 name: normalized accuracy source: url: >- https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fluently-lm/FluentlyLM-Prinum 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: 54 name: exact match source: url: >- https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fluently-lm/FluentlyLM-Prinum 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: 18.23 name: acc_norm source: url: >- https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fluently-lm/FluentlyLM-Prinum 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: 17.26 name: acc_norm source: url: >- https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fluently-lm/FluentlyLM-Prinum 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: 53.42 name: accuracy source: url: >- https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fluently-lm/FluentlyLM-Prinum name: Open LLM Leaderboard --- # huihui-ai/FluentlyLM-Prinum-abliterated This is an uncensored version of [fluently-lm/FluentlyLM-Prinum](https://huggingface.co./fluently-lm/FluentlyLM-Prinum) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. ## Use with ollama You can use [huihui_ai/fluentlylm-prinum-abliterated](https://ollama.com/huihui_ai/fluentlylm-prinum-abliterated) directly ``` ollama run huihui_ai/fluentlylm-prinum-abliterated ``` ### Donation If you like it, please click 'like' and follow us for more updates. You can follow [x.com/support_huihui](https://x.com/support_huihui) to get the latest model information from huihui.ai. ##### Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin: ``` bc1qqnkhuchxw0zqjh2ku3lu4hq45hc6gy84uk70ge ```