--- license: llama3.1 library_name: transformers tags: - mergekit - merge base_model: - nvidia/Llama-3.1-Nemotron-70B-Instruct-HF - mlabonne/Llama-3-70B-Instruct-abliterated-LORA model-index: - name: Llama-3.1-Nemotron-lorablated-70B 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: 71.47 name: strict accuracy source: url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Llama-3.1-Nemotron-lorablated-70B 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: 48.06 name: normalized accuracy source: url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Llama-3.1-Nemotron-lorablated-70B 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: 23.34 name: exact match source: url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Llama-3.1-Nemotron-lorablated-70B 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: 0.89 name: acc_norm source: url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Llama-3.1-Nemotron-lorablated-70B 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: 14.92 name: acc_norm source: url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Llama-3.1-Nemotron-lorablated-70B 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: 43.46 name: accuracy source: url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Llama-3.1-Nemotron-lorablated-70B name: Open LLM Leaderboard --- ![image/png](https://huggingface.co./nbeerbower/Llama-3.1-Nemotron-lorablated-70B/resolve/main/nemotron.png?download=true) # Llama-3.1-Nemotron-lorablated-70B An uncensored version of [nvidia/Llama-3.1-Nemotron-70B-Instruct-HF](https://huggingface.co./nvidia/Llama-3.1-Nemotron-70B-Instruct-HF) created by merging [mlabonne/Llama-3-70B-Instruct-abliterated-LORA](https://huggingface.co./mlabonne/Llama-3-70B-Instruct-abliterated-LORA) using [task arithmetic](https://arxiv.org/abs/2212.04089). ## Method This model was created using [mergekit](https://github.com/cg123/mergekit). From Ubuntu 24.04 (as root): ``` apt update apt install pipx git clone https://github.com/arcee-ai/mergekit.git cd mergekit && pipx install -e . mergekit-yaml config.yaml Llama-3.1-Nemotron-lorablated-70B --allow-crimes --lora-merge-cache=./cache ``` See [@mlabonne](https://huggingface.co./mlabonne)'s [Llama-3.1-70B-Instruct-lorablated](https://huggingface.co./mlabonne/Llama-3.1-70B-Instruct-lorablated) for more details on how the LoRA was extracted. ### Configuration The following YAML configuration was used to produce this model: ```yaml base_model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF+mlabonne/Llama-3-70B-Instruct-abliterated-LORA dtype: bfloat16 merge_method: task_arithmetic parameters: normalize: false slices: - sources: - layer_range: [0, 80] model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF+mlabonne/Llama-3-70B-Instruct-abliterated-LORA parameters: weight: 1.0 ``` ### Acknowlegements Thanks to [@mlabonne](https://huggingface.co./mlabonne), [@grimjim](https://huggingface.co./grimjim), and [@failspy](https://huggingface.co./failspy) for pioneering this technique for uncensoring models. Compute provided by [Hetzner](https://www.hetzner.com/) and funded by [Schneewolf Labs](https://schneewolflabs.com/). # [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/details_nbeerbower__Llama-3.1-Nemotron-lorablated-70B) | Metric |Value| |-------------------|----:| |Avg. |33.69| |IFEval (0-Shot) |71.47| |BBH (3-Shot) |48.06| |MATH Lvl 5 (4-Shot)|23.34| |GPQA (0-shot) | 0.89| |MuSR (0-shot) |14.92| |MMLU-PRO (5-shot) |43.46|