metadata
base_model:
- Bingguang/FunReason-MT
- openfree/Darwin-Qwen3-4B
- ricdomolm/mini-coder-4b
- minchyeom/Qwaifu
tags:
- merge
- mergekit
- lazymergekit
- Bingguang/FunReason-MT
- openfree/Darwin-Qwen3-4B
- ricdomolm/mini-coder-4b
- minchyeom/Qwaifu
Qwen3-4B-Mini-Merge
Qwen3-4B-Mini-Merge is a merge of the following models using LazyMergekit:
🧩 Configuration
models:
- model: Bingguang/FunReason-MT
parameters:
density: 0.3
weight: 0.3
- model: openfree/Darwin-Qwen3-4B
parameters:
density: 0.3
weight: 0.3
- model: ricdomolm/mini-coder-4b
parameters:
density: 0.3
weight: 0.3
- model: minchyeom/Qwaifu
parameters:
density: 0.5
weight: 0.5
merge_method: ties
base_model: huihui-ai/Huihui-Qwen3-4B-Instruct-2507-abliterated
parameters:
normalize: true
dtype: float16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "bunnycore/Qwen3-4B-Mini-Merge"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])