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---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- NousResearch/Hermes-3-Llama-3.1-70B
- mlabonne/Llama-3-70B-Instruct-abliterated-LORA
model-index:
- name: Hermes-3-Llama-3.1-70B-lorablated
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: 71.44
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Hermes-3-Llama-3.1-70B-lorablated
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: 52.34
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Hermes-3-Llama-3.1-70B-lorablated
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: 13.82
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Hermes-3-Llama-3.1-70B-lorablated
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: 13.2
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Hermes-3-Llama-3.1-70B-lorablated
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: 22.02
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Hermes-3-Llama-3.1-70B-lorablated
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: 41.37
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Hermes-3-Llama-3.1-70B-lorablated
name: Open LLM Leaderboard
---
# 🪽 Hermes-3-Llama-3.1-70B-lorablated
<center>8B version: <a href="https://huggingface.co/mlabonne/Hermes-3-Llama-3.1-8B-lorablated/"><i>mlabonne/Hermes-3-Llama-3.1-8B-lorablated</i></a></center>
This is an uncensored version of [NousResearch/Hermes-3-Llama-3.1-70B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-70B) using lorablation.
You can see in the following example how Hermes 3 refuses to answer a legitimate question while the abliterated model complies:
The recipe is based on @grimjim's [grimjim/Llama-3.1-8B-Instruct-abliterated_via_adapter](https://huggingface.co/grimjim/Llama-3.1-8B-Instruct-abliterated_via_adapter) (special thanks):
1. **Extraction**: We extract a LoRA adapter by comparing two models: a censored Llama 3 ([meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct)) and an abliterated Llama 3.1 ([failspy/Meta-Llama-3.1-70B-Instruct-abliterated](https://huggingface.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated)).
2. **Merge**: We merge this new LoRA adapter using [task arithmetic](https://arxiv.org/abs/2212.04089) to the censored [NousResearch/Hermes-3-Llama-3.1-70B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-70B) to abliterate it.
See [this article](https://huggingface.co/blog/mlabonne/abliteration) to learn more about abliteration.
## ⚡ Quantization
* **GGUF**: https://huggingface.co/mlabonne/Hermes-3-Llama-3.1-70B-lorablated-GGUF
## 🧩 Configuration
This model was merged using the [task arithmetic](https://arxiv.org/abs/2212.04089) merge method using [NousResearch/Hermes-3-Llama-3.1-70B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-70B) + Llama-3.1-70B-Instruct-abliterated-LORA as a base.
The following YAML configuration was used to produce this model:
```yaml
base_model: NousResearch/Hermes-3-Llama-3.1-70B+mlabonne/Llama-3.1-70B-Instruct-abliterated-LORA
dtype: bfloat16
merge_method: task_arithmetic
parameters:
normalize: false
slices:
- sources:
- layer_range: [0, 32]
model: NousResearch/Hermes-3-Llama-3.1-70B+mlabonne/Llama-3.1-70B-Instruct-abliterated-LORA
parameters:
weight: 1.0
```
You can reproduce this model using the following commands:
```bash
# Setup
git clone https://github.com/arcee-ai/mergekit.git
cd mergekit && pip install -e .
pip install bitsandbytes
# Merge using previous config
mergekit-yaml config.yaml Hermes-3-Llama-3.1-70B-lorablated --allow-crimes --lora-merge-cache=./cache
```
# [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_mlabonne__Hermes-3-Llama-3.1-70B-lorablated)
| Metric |Value|
|-------------------|----:|
|Avg. |35.70|
|IFEval (0-Shot) |71.44|
|BBH (3-Shot) |52.34|
|MATH Lvl 5 (4-Shot)|13.82|
|GPQA (0-shot) |13.20|
|MuSR (0-shot) |22.02|
|MMLU-PRO (5-shot) |41.37|
|