transformers safetensors qwen2 text-generation chat abliterated uncensored mergekit merge conversational en arxiv:2203.05482 base_model:Qwen/QwQ-32B-Preview base_model:merge:Qwen/QwQ-32B-Preview base_model:huihui-ai/QwQ-32B-Preview-abliterated base_model:merge:huihui-ai/QwQ-32B-Preview-abliterated license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model:
- Qwen/QwQ-32B-Preview
- huihui-ai/QwQ-32B-Preview-abliterated
language:
- en
library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/pipihand01/QwQ-32B-Preview-abliterated-linear50/blob/main/LICENSE
tags:
- chat
- abliterated
- uncensored
- mergekit
- merge
---
This is a 50% abliterated model obtained from linear-weighted merging [Qwen/QwQ-32B-Preview](https://huggingface.co/Qwen/QwQ-32B-Preview) (weight: 0.5) and [huihui-ai/QwQ-32B-Preview-abliterated](https://huggingface.co/huihui-ai/QwQ-32B-Preview-abliterated) (weight: 0.5), using [mergekit](https://github.com/arcee-ai/mergekit).

This is an experimental model, and from my preliminary experiments, this gives more natural result than Qwen's original model for sensitive contents while still maintaining refusal capability.

Base on some of my experiments, I found when it comes to "sensitive contents" generation, the more percentage of abliteration, the more peace but direct result it might get, and the less "conflict and disagreement".

To get best effect when it comes to "uncensoring", for low percentage of abliteration mixture like this one, it would be better to use it in RP or story writing without using official or other "AI assistant" prompts. E.g. You should use chat mode instead of instruct mode in [Text generation web UI](https://github.com/oobabooga/text-generation-webui), and avoid prompting like AI assistant.

From my experiments, this model removes some artificial wording of the "censorship", when prompting for RP or story writing correctly.

I also offer other percentages of abliteration so you can try which one best suits your use case.

Or you may use [this LoRA](https://huggingface.co/pipihand01/QwQ-32B-Preview-abliterated-lora-rank32) if you know how to apply LoRA and adjust its weight for the app you use.

**NOTE: I bear no responsibility for any output of this model. When properly prompted, this model may generate contents that are not suitable in some situations. Use it with your own caution.**

---
# pipihand01/QwQ-32B-Preview-abliterated-linear50

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the [linear](https://arxiv.org/abs/2203.05482) merge method.

### Models Merged

The following models were included in the merge:
* [Qwen/QwQ-32B-Preview](https://huggingface.co/Qwen/QwQ-32B-Preview)
* [huihui-ai/QwQ-32B-Preview-abliterated](https://huggingface.co/huihui-ai/QwQ-32B-Preview-abliterated)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: Qwen/QwQ-32B-Preview
    parameters:
      weight: 0.5
  - model: huihui-ai/QwQ-32B-Preview-abliterated
    parameters:
      weight: 0.5
merge_method: linear
dtype: bfloat16
```
