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Model: ertghiu256/Qwen3-4b-tcomanr-merge-v2.1 Source: Original Platform
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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Tcomanr-V2_1-4.0B-IQ4_NL.gguf filter=lfs diff=lfs merge=lfs -text
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README.md
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README.md
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---
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base_model:
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- ertghiu256/qwen3-multi-reasoner
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- ertghiu256/deepseek-r1-0528-distilled-qwen3
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- huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated
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- ertghiu256/qwen3-4b-code-reasoning
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- Qwen/Qwen3-4B-Thinking-2507
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- ertghiu256/qwen3-math-reasoner
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- POLARIS-Project/Polaris-4B-Preview
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- Tesslate/UIGEN-T3-4B-Preview-MAX
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- ertghiu256/Qwen3-Hermes-4b
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- ertghiu256/qwen-3-4b-mixture-of-thought
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- ValiantLabs/Qwen3-4B-ShiningValiant3
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- ValiantLabs/Qwen3-4B-Esper3
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library_name: transformers
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tags:
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- mergekit
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- merge
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- thinking
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- think
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- reasoning
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- reason
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- code
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- math
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- qwen
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- qwen3
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new_version: ertghiu256/Qwen3-4b-tcomanr-merge-v2.2
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---
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# Ties merged COde MAth aNd Reasoning model
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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This model is a revision of the [ertghiu256/Qwen3-4b-tcomanr-merge-v2](https://huggingface.co/ertghiu256/Qwen3-4b-tcomanr-merge-v2/)
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This model aims to combine the code and math capabilities by merging Qwen 3 2507 with multiple Qwen 3 finetunes.
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# How to run
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You can run this model by using multiple interface choices
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## Transformers
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As the qwen team suggested to use
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "ertghiu256/Qwen3-4b-tcomanr-merge-v2.1"
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# load the tokenizer and the model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype="auto",
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device_map="auto"
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)
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# prepare the model input
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prompt = "Give me a short introduction to large language model."
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messages = [
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True,
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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# conduct text completion
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=32768
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)
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output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
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# parsing thinking content
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try:
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# rindex finding 151668 (</think>)
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index = len(output_ids) - output_ids[::-1].index(151668)
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except ValueError:
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index = 0
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thinking_content = tokenizer.decode(output_ids[:index], skip_special_tokens=True).strip("\n")
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content = tokenizer.decode(output_ids[index:], skip_special_tokens=True).strip("\n")
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print("thinking content:", thinking_content) # no opening <think> tag
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print("content:", content)
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```
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## Vllm
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Run this command
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```bash
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vllm serve ertghiu256/Qwen3-4b-tcomanr-merge-v2.1 --enable-reasoning --reasoning-parser deepseek_r1
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```
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## Sglang
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Run this command
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```bash
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python -m sglang.launch_server --model-path ertghiu256/Qwen3-4b-tcomanr-merge-v2.1 --reasoning-parser deepseek-r1
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```
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## llama.cpp
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Run this command
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```bash
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llama-server --hf-repo ertghiu256/Qwen3-4b-tcomanr-merge-v2.1
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```
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or
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```bash
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||||
llama-cli --hf ertghiu256/Qwen3-4b-tcomanr-merge-v2.1
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```
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## Ollama
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Run this command
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```bash
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ollama run hf.co/ertghiu256/Qwen3-4b-tcomanr-merge-v2.1:Q8_0
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```
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or
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||||
```bash
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ollama run hf.co/ertghiu256/Qwen3-4b-tcomanr-merge-v2.1:IQ4_NL
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```
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## LM Studio
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||||
Search
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||||
```
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||||
ertghiu256/Qwen3-4b-tcomanr-merge-v2.1
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```
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in the lm studio model search list then download
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||||
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### Recomended parameters
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```
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temp: 0.6
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num_ctx: ≥8192
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top_p: 0.9
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top_k: 20
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Repeat Penalty: 1.1
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```
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### Merge Method
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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.
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### Models Merged
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The following models were included in the merge:
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* [ertghiu256/qwen3-multi-reasoner](https://huggingface.co/ertghiu256/qwen3-multi-reasoner)
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* [ertghiu256/deepseek-r1-0528-distilled-qwen3](https://huggingface.co/ertghiu256/deepseek-r1-0528-distilled-qwen3)
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* [huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated](https://huggingface.co/huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated)
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* [ertghiu256/qwen3-4b-code-reasoning](https://huggingface.co/ertghiu256/qwen3-4b-code-reasoning)
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* [ertghiu256/qwen3-math-reasoner](https://huggingface.co/ertghiu256/qwen3-math-reasoner)
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* [POLARIS-Project/Polaris-4B-Preview](https://huggingface.co/POLARIS-Project/Polaris-4B-Preview)
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||||
* [Tesslate/UIGEN-T3-4B-Preview-MAX](https://huggingface.co/Tesslate/UIGEN-T3-4B-Preview-MAX)
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||||
* [ertghiu256/Qwen3-Hermes-4b](https://huggingface.co/ertghiu256/Qwen3-Hermes-4b)
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||||
* [ertghiu256/qwen-3-4b-mixture-of-thought](https://huggingface.co/ertghiu256/qwen-3-4b-mixture-of-thought)
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||||
* [ValiantLabs/Qwen3-4B-ShiningValiant3](https://huggingface.co/ValiantLabs/Qwen3-4B-ShiningValiant3)
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||||
* [ValiantLabs/Qwen3-4B-Esper3](https://huggingface.co/ValiantLabs/Qwen3-4B-Esper3)
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||||
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### Configuration
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||||
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The following YAML configuration was used to produce this model:
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||||
```yaml
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models:
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- model: ertghiu256/qwen3-math-reasoner
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parameters:
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weight: 0.8
|
||||
- model: ertghiu256/qwen3-4b-code-reasoning
|
||||
parameters:
|
||||
weight: 0.9
|
||||
- model: ertghiu256/qwen-3-4b-mixture-of-thought
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||||
parameters:
|
||||
weight: 0.9
|
||||
- model: POLARIS-Project/Polaris-4B-Preview
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||||
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
|
||||
merge_method: ties
|
||||
base_model: Qwen/Qwen3-4B-Thinking-2507
|
||||
parameters:
|
||||
normalize: true
|
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int8_mask: true
|
||||
lambda: 1.0
|
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dtype: float16
|
||||
|
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```
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Tcomanr-V2_1-4.0B-IQ4_NL.gguf
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Tcomanr-V2_1-4.0B-Q8_0.gguf
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config.json
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config.json
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{
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"architectures": [
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"Qwen3ForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"eos_token_id": 151645,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 2560,
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"initializer_range": 0.02,
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"intermediate_size": 9728,
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"max_position_embeddings": 262144,
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"max_window_layers": 36,
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"model_type": "qwen3",
|
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"num_attention_heads": 32,
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"num_hidden_layers": 36,
|
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"num_key_value_heads": 8,
|
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"rms_norm_eps": 1e-06,
|
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"rope_scaling": null,
|
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"rope_theta": 5000000,
|
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"sliding_window": null,
|
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"tie_word_embeddings": true,
|
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"torch_dtype": "float16",
|
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"transformers_version": "4.51.3",
|
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"use_cache": true,
|
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"use_sliding_window": false,
|
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"vocab_size": 151936
|
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}
|
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mergekit_config.yml
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mergekit_config.yml
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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
|
||||
merge_method: ties
|
||||
base_model: Qwen/Qwen3-4B-Thinking-2507
|
||||
parameters:
|
||||
normalize: true
|
||||
int8_mask: true
|
||||
lambda: 1.0
|
||||
dtype: float16
|
||||
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model-00001-of-00002.safetensors
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tokenizer.json
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tokenizer.json
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tokenizer_config.json
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{
|
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"add_prefix_space": false,
|
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"added_tokens_decoder": {
|
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"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
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|
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|
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|
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|
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|
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"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151665": {
|
||||
"content": "<tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151666": {
|
||||
"content": "</tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151667": {
|
||||
"content": "<think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151668": {
|
||||
"content": "</think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n {%- endif %}\n {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n {%- set index = (messages|length - 1) - loop.index0 %}\n {%- if ns.multi_step_tool and message.role == \"user\" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n {%- if message.content is string %}\n {%- set content = message.content %}\n {%- else %}\n {%- set content = '' %}\n {%- endif %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is string %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- else %}\n {%- if '</think>' in content %}\n {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n {%- endif %}\n {%- endif %}\n {%- if loop.index0 > ns.last_query_index %}\n {%- if loop.last or (not loop.last and reasoning_content) %}\n {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- if message.tool_calls %}\n {%- for tool_call in message.tool_calls %}\n {%- if (loop.first and content) or (not loop.first) %}\n {{- '\\n' }}\n {%- endif %}\n {%- if tool_call.function %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {%- if tool_call.arguments is string %}\n {{- tool_call.arguments }}\n {%- else %}\n {{- tool_call.arguments | tojson }}\n {%- endif %}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n<think>\\n' }}\n{%- endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"model_max_length": 262144,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null,
|
||||
"add_bos_token": false
|
||||
}
|
||||
Reference in New Issue
Block a user