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---
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|
|