README.md

---
base_model:
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B-Instruct
tags:
- merge
- mergekit
- lazymergekit
- Qwen/Qwen2.5-1.5B-Instruct
---

# Qwen2.5-2B-Instruct

Qwen2.5-2B-Instruct is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)

## 🧩 Configuration

```yaml
dtype: bfloat16
merge_method: passthrough
slices:
- sources:
  - layer_range: [0, 2]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [1, 3]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [2, 4]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [3, 5]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [4, 6]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [5, 7]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [6, 8]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [7, 9]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [8, 10]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [9, 11]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [10, 12]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [11, 13]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [12, 14]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [13, 15]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [14, 16]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [16, 18]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [17, 19]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [18, 20]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [19, 21]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [20, 22]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [21, 23]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [22, 24]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [23, 25]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [24, 26]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [25, 27]
    model: Qwen/Qwen2.5-1.5B-Instruct
- sources:
  - layer_range: [26, 28]
    model: Qwen/Qwen2.5-1.5B-Instruct
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "win10/Qwen2.5-2B-Instruct"
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"])
```