---
base_model:
- huihui-ai/QwQ-32B-abliterated
- zetasepic/Rombo-LLM-V3.1-QWQ-32b-abliterated
- Qwen/Qwen2.5-32B
- DataSoul/QAQ-32B-merge3
library_name: transformers
tags:
- mergekit
- merge
language:
- zho
- eng
- fra
- spa
- por
- deu
- ita
- rus
- jpn
- kor
- vie
- tha
- ara
---
Unstable "thinking" and "reasoning" models, which typically respond in four scenarios:

1 (occasionally), <think>...</think> answer.

2 (occasionally), <think>... answer.

3 (occasionally), <think>... .

4 (rarely), answer.

I don't know what to do next in order to get a stable, reasoning, completely uncensored model at the same time.
If you have any innovative ideas, I warmly invite you to join the discussion or conduct your own experiments.

More recommended [DataSoul/QAQ-32B-merge3](https://huggingface.co/DataSoul/QAQ-32B-merge3)But it is still not a 'thinking' model.


# merge

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 [SCE](https://arxiv.org/abs/2408.07990) merge method using [Qwen/Qwen2.5-32B](https://huggingface.co/Qwen/Qwen2.5-32B) as a base.

### Models Merged

The following models were included in the merge:
* [huihui-ai/QwQ-32B-abliterated](https://huggingface.co/huihui-ai/QwQ-32B-abliterated)
* [zetasepic/Rombo-LLM-V3.1-QWQ-32b-abliterated](https://huggingface.co/zetasepic/Rombo-LLM-V3.1-QWQ-32b-abliterated)
* [DataSoul/QAQ-32B-merge3](https://huggingface.co/DataSoul/QAQ-32B-merge3)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  # Pivot model
  - model: Qwen/Qwen2.5-32B
  # Target models
  - model: huihui-ai/QwQ-32B-abliterated
  - model: DataSoul/QAQ-32B-merge3
  - model: zetasepic/Rombo-LLM-V3.1-QWQ-32b-abliterated
merge_method: sce
base_model: Qwen/Qwen2.5-32B
tokenizer_source: zetasepic/Rombo-LLM-V3.1-QWQ-32b-abliterated
parameters:
  select_topk: 1.0
dtype: bfloat16

```