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Llama-3.1-Nemotron-lorablated-70B - GGUF
- Model creator: https://huggingface.co/nbeerbower/
- Original model: https://huggingface.co/nbeerbower/Llama-3.1-Nemotron-lorablated-70B/
Original model description:
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
Llama-3.1-Nemotron-lorablated-70B
An uncensored version of nvidia/Llama-3.1-Nemotron-70B-Instruct-HF created by merging mlabonne/Llama-3-70B-Instruct-abliterated-LORA using task arithmetic.
Method
This model was created using 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's 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:
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, @grimjim, and @failspy for pioneering this technique for uncensoring models.
Compute provided by Hetzner and funded by Schneewolf Labs.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| 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 |
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