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---
base_model:
- huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated
- Tesslate/UIGEN-T3-4B-Preview-MAX
- ValiantLabs/Qwen3-4B-Esper3
- ValiantLabs/Qwen3-4B-ShiningValiant3
- ertghiu256/Qwen3-Hermes-4b
- ertghiu256/qwen3-math-reasoner
- ertghiu256/deepseek-r1-0528-distilled-qwen3
- ertghiu256/qwen-3-4b-mixture-of-thought
- Qwen/Qwen3-4B-Thinking-2507
- POLARIS-Project/Polaris-4B-Preview
- ertghiu256/qwen3-multi-reasoner
- ertghiu256/qwen3-4b-code-reasoning
library_name: transformers
tags:
- mergekit
- merge
- thinking
- think
- reasoning
- reason
- code
- math
- qwen
- qwen3
new_version: ertghiu256/Qwen3-4b-tcomanr-merge-v2.3
---
# Ties merged COde MAth aNd Reasoning model
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
This model is a revision of the [ertghiu256/Qwen3-4b-tcomanr-merge-v2](https://huggingface.co/ertghiu256/Qwen3-4b-tcomanr-merge-v2/)
This model aims to combine the code and math capabilities by merging Qwen 3 2507 with multiple Qwen 3 finetunes.
# How to run
You can run this model by using multiple interface choices
## Transformers
As the qwen team suggested to use
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "ertghiu256/Qwen3-4b-tcomanr-merge-v2.2"
# load the tokenizer and the model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype="auto",
device_map="auto"
)
# prepare the model input
prompt = "Give me a short introduction to large language model."
messages = [
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True,
)
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
# conduct text completion
generated_ids = model.generate(
**model_inputs,
max_new_tokens=32768
)
output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
# parsing thinking content
try:
# rindex finding 151668 (</think>)
index = len(output_ids) - output_ids[::-1].index(151668)
except ValueError:
index = 0
thinking_content = tokenizer.decode(output_ids[:index], skip_special_tokens=True).strip("\n")
content = tokenizer.decode(output_ids[index:], skip_special_tokens=True).strip("\n")
print("thinking content:", thinking_content) # no opening <think> tag
print("content:", content)
```
## Vllm
Run this command
```bash
vllm serve ertghiu256/Qwen3-4b-tcomanr-merge-v2.2 --enable-reasoning --reasoning-parser deepseek_r1
```
## Sglang
Run this command
```bash
python -m sglang.launch_server --model-path ertghiu256/Qwen3-4b-tcomanr-merge-v2.2 --reasoning-parser deepseek-r1
```
## llama.cpp
Run this command
```bash
llama-server --hf-repo ertghiu256/Qwen3-4b-tcomanr-merge-v2.2
```
or
```bash
llama-cli --hf ertghiu256/Qwen3-4b-tcomanr-merge-v2.2
```
## Ollama
Run this command
```bash
ollama run hf.co/ertghiu256/Qwen3-4b-tcomanr-merge-v2.2:Q8_0
```
or
```bash
ollama run hf.co/ertghiu256/Qwen3-4b-tcomanr-merge-v2.2:Q5_K_M
```
## LM Studio
Search
```
ertghiu256/Qwen3-4b-tcomanr-merge-v2.2
```
in the lm studio model search list then download
### Recomended parameters
```
temp: 0.7
num_ctx: ≥8192
top_p: 0.95
top_k: 40
Repeat Penalty: 1.1
```
### Merge Method
This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [Qwen/Qwen3-4B-Thinking-2507](https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507) as a base.
### Models Merged
The following models were included in the merge:
* [huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated](https://huggingface.co/huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated)
* [Tesslate/UIGEN-T3-4B-Preview-MAX](https://huggingface.co/Tesslate/UIGEN-T3-4B-Preview-MAX)
* [ValiantLabs/Qwen3-4B-Esper3](https://huggingface.co/ValiantLabs/Qwen3-4B-Esper3)
* [ValiantLabs/Qwen3-4B-ShiningValiant3](https://huggingface.co/ValiantLabs/Qwen3-4B-ShiningValiant3)
* [ertghiu256/Qwen3-Hermes-4b](https://huggingface.co/ertghiu256/Qwen3-Hermes-4b)
* [ertghiu256/qwen3-math-reasoner](https://huggingface.co/ertghiu256/qwen3-math-reasoner)
* [ertghiu256/deepseek-r1-0528-distilled-qwen3](https://huggingface.co/ertghiu256/deepseek-r1-0528-distilled-qwen3)
* [ertghiu256/qwen-3-4b-mixture-of-thought](https://huggingface.co/ertghiu256/qwen-3-4b-mixture-of-thought)
* [POLARIS-Project/Polaris-4B-Preview](https://huggingface.co/POLARIS-Project/Polaris-4B-Preview)
* [ertghiu256/qwen3-multi-reasoner](https://huggingface.co/ertghiu256/qwen3-multi-reasoner)
* [ertghiu256/qwen3-4b-code-reasoning](https://huggingface.co/ertghiu256/qwen3-4b-code-reasoning)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
- model: ertghiu256/qwen3-math-reasoner
parameters:
weight: 0.8
- model: ertghiu256/qwen3-4b-code-reasoning
parameters:
weight: 0.9
- model: ertghiu256/qwen-3-4b-mixture-of-thought
parameters:
weight: 0.9
- model: POLARIS-Project/Polaris-4B-Preview
parameters:
weight: 0.9
- model: ertghiu256/qwen3-multi-reasoner
parameters:
weight: 0.8
- model: ertghiu256/Qwen3-Hermes-4b
parameters:
weight: 0.8
- model: ValiantLabs/Qwen3-4B-Esper3
parameters:
weight: 0.8
- model: Tesslate/UIGEN-T3-4B-Preview-MAX
parameters:
weight: 0.9
- model: ValiantLabs/Qwen3-4B-ShiningValiant3
parameters:
weight: 0.6
- model: ertghiu256/deepseek-r1-0528-distilled-qwen3
parameters:
weight: 0.1
- model: huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated
parameters:
weight: 0.6
- model: Qwen/Qwen3-4B-Thinking-2507
parameters:
weight: 0.9
merge_method: ties
base_model: Qwen/Qwen3-4B-Thinking-2507
parameters:
normalize: true
int8_mask: true
lambda: 1.0
dtype: float16
```