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---
language:
- en
license: apache-2.0
tags:
- chat
pipeline_tag: text-generation
model-index:
- name: Qwen2-7B-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: 58.37
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=natong19/Qwen2-7B-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: 37.75
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=natong19/Qwen2-7B-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: 10.27
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=natong19/Qwen2-7B-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: 6.82
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=natong19/Qwen2-7B-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: 8.93
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=natong19/Qwen2-7B-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: 31.58
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=natong19/Qwen2-7B-Instruct-abliterated
name: Open LLM Leaderboard
---
# Qwen2-7B-Instruct-abliterated
## Introduction
Abliterated version of [Qwen2-7B-Instruct](https://huggingface.co/Qwen/Qwen2-7B-Instruct) using [failspy](https://huggingface.co/failspy)'s notebook.
The model's strongest refusal directions have been ablated via weight orthogonalization, but the model may still refuse your request, misunderstand your intent, or provide unsolicited advice regarding ethics or safety.
## Quickstart
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "natong19/Qwen2-7B-Instruct-abliterated"
device = "cuda" # the device to load the model onto
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype="auto",
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_id)
prompt = "Give me a short introduction to large language model."
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(device)
generated_ids = model.generate(
model_inputs.input_ids,
max_new_tokens=256
)
generated_ids = [
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)
```
## Evaluation
Evaluation framework: lm-evaluation-harness 0.4.2
| Datasets | Qwen2-7B-Instruct | Qwen2-7B-Instruct-abliterated |
| :--- | :---: | :---: |
| ARC (25-shot) | 62.5 | 62.5 |
| GSM8K (5-shot) | 73.0 | 72.2 |
| HellaSwag (10-shot) | 81.8 | 81.7 |
| MMLU (5-shot) | 70.7 | 70.5 |
| TruthfulQA (0-shot) | 57.3 | 55.0 |
| Winogrande (5-shot) | 76.2 | 77.4 |
# [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_natong19__Qwen2-7B-Instruct-abliterated)
| Metric |Value|
|-------------------|----:|
|Avg. |25.62|
|IFEval (0-Shot) |58.37|
|BBH (3-Shot) |37.75|
|MATH Lvl 5 (4-Shot)|10.27|
|GPQA (0-shot) | 6.82|
|MuSR (0-shot) | 8.93|
|MMLU-PRO (5-shot) |31.58|
|