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-merge3But it is still not a 'thinking' model.
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the SCE merge method using Qwen/Qwen2.5-32B as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
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