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---
license: llama3.1
library_name: transformers
tags:
- abliterated
- uncensored
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
model-index:
- name: Meta-Llama-3.1-8B-Instruct-abliterated
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: 73.29
name: strict accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
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: 27.13
name: normalized accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
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: 6.42
name: exact match
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
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=mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
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: 3.21
name: acc_norm
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
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: 27.81
name: accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
name: Open LLM Leaderboard
---
# 🦙 Meta-Llama-3.1-8B-Instruct-abliterated
<center>🦙 <a href="https://huggingface.co./mlabonne/Llama-3.1-70B-Instruct-lorablated"><i>Llama 3.1 70B Instruct lorablated</i></a></center>
This is an uncensored version of Llama 3.1 8B Instruct created with abliteration (see [this article](https://huggingface.co./blog/mlabonne/abliteration) to know more about it).
Special thanks to [@FailSpy](https://huggingface.co./failspy) for the original code and technique. Please follow him if you're interested in abliterated models.
## ⚡️ Quantization
Thanks to ZeroWw and Apel-sin for the quants.
* **New GGUF**: https://huggingface.co./mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated-GGUF
* **ZeroWw GGUF**: https://huggingface.co./ZeroWw/Meta-Llama-3.1-8B-Instruct-abliterated-GGUF
* **EXL2**: https://huggingface.co./Apel-sin/llama-3.1-8B-abliterated-exl2
# [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__Meta-Llama-3.1-8B-Instruct-abliterated)
| Metric |Value|
|-------------------|----:|
|Avg. |23.13|
|IFEval (0-Shot) |73.29|
|BBH (3-Shot) |27.13|
|MATH Lvl 5 (4-Shot)| 6.42|
|GPQA (0-shot) | 0.89|
|MuSR (0-shot) | 3.21|
|MMLU-PRO (5-shot) |27.81|
|