--- base_model: - ertghiu256/qwen3-4b-code-reasoning - Qwen/Qwen3-4B - Tesslate/UIGEN-T3-4B-Preview-MAX - ertghiu256/qwen-3-4b-mixture-of-thought - POLARIS-Project/Polaris-4B-Preview - ertghiu256/qwen3-math-reasoner - ertghiu256/qwen3-multi-reasoner - ValiantLabs/Qwen3-4B-Esper3 - ValiantLabs/Qwen3-4B-ShiningValiant3 - prithivMLmods/Crux-Qwen3_OpenThinking-4B library_name: transformers tags: - mergekit - merge --- # 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 aims to combine the code and math capabilities by merging 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" # 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, enable_thinking=True # Switches between thinking and non-thinking modes. Default is 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 () 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) print("content:", content) ``` ## vllm Run this command ```bash vllm serve ertghiu256/Qwen3-4b-tcomanr-merge --enable-reasoning --reasoning-parser deepseek_r1 ``` ## Sglang Run this command ```bash python -m sglang.launch_server --model-path ertghiu256/Qwen3-4b-tcomanr-merge --reasoning-parser deepseek-r1 ``` ## llama.cpp Run this command ```bash .\llama-server --hf-repo hf.co/ertghiu256/Qwen3-4b-tcomanr-merge ``` ## ollama Run this command ```bash ollama run hf.co/ertghiu256/Qwen3-4b-tcomanr-merge ``` ## lm studio Search ``` ertghiu256/Qwen3-4b-tcomanr-merge ``` in the lm studio model search list then download ### Merge Details This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [Qwen/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B) as a base. #### Models: The following models were included in the merge: * [ertghiu256/qwen3-4b-code-reasoning](https://huggingface.co/ertghiu256/qwen3-4b-code-reasoning) * [Tesslate/UIGEN-T3-4B-Preview-MAX](https://huggingface.co/Tesslate/UIGEN-T3-4B-Preview-MAX) * [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-math-reasoner](https://huggingface.co/ertghiu256/qwen3-math-reasoner) * [ertghiu256/qwen3-multi-reasoner](https://huggingface.co/ertghiu256/qwen3-multi-reasoner) * [ValiantLabs/Qwen3-4B-Esper3](https://huggingface.co/ValiantLabs/Qwen3-4B-Esper3) * [ValiantLabs/Qwen3-4B-ShiningValiant3](https://huggingface.co/ValiantLabs/Qwen3-4B-ShiningValiant3) * [prithivMLmods/Crux-Qwen3_OpenThinking-4B](https://huggingface.co/prithivMLmods/Crux-Qwen3_OpenThinking-4B) #### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: ertghiu256/qwen3-math-reasoner parameters: weight: 0.7 - model: ertghiu256/qwen3-4b-code-reasoning parameters: weight: 0.8 - model: ertghiu256/qwen-3-4b-mixture-of-thought parameters: weight: 0.9 - model: POLARIS-Project/Polaris-4B-Preview parameters: weight: 0.7 - model: ertghiu256/qwen3-multi-reasoner parameters: weight: 0.8 - model: ValiantLabs/Qwen3-4B-Esper3 parameters: weight: 0.8 - model: Tesslate/UIGEN-T3-4B-Preview-MAX parameters: weight: 0.8 - model: ValiantLabs/Qwen3-4B-ShiningValiant3 parameters: weight: 0.9 - model: prithivMLmods/Crux-Qwen3_OpenThinking-4B parameters: weight: 0.4 merge_method: ties base_model: Qwen/Qwen3-4B parameters: normalize: true int8_mask: true dtype: float16 ```