---
base_model:
- Mohaddz/Qwen3-14B-Instruct-LoRA-1310-Merged
- Mohaddz/Qwen3-14B-Instruct-LoRA-1310-insta500K-Merged
- Qwen/Qwen3-14B
tags:
- merge
- mergekit
- lazymergekit
- Mohaddz/Qwen3-14B-Instruct-LoRA-1310-Merged
- Mohaddz/Qwen3-14B-Instruct-LoRA-1310-insta500K-Merged
- Qwen/Qwen3-14B
---

# Qwen3-14B-Instruct-1310-insta500K-think-orca-TIES

Qwen3-14B-Instruct-1310-insta500K-think-orca-TIES is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Mohaddz/Qwen3-14B-Instruct-LoRA-1310-Merged](https://huggingface.co/Mohaddz/Qwen3-14B-Instruct-LoRA-1310-Merged)
* [Mohaddz/Qwen3-14B-Instruct-LoRA-1310-insta500K-Merged](https://huggingface.co/Mohaddz/Qwen3-14B-Instruct-LoRA-1310-insta500K-Merged)
* [Qwen/Qwen3-14B](https://huggingface.co/Qwen/Qwen3-14B)

## 🧩 Configuration

```yaml
   models:
     - model: Mohaddz/Qwen3-14B-Instruct-LoRA-1310-Merged
       parameters:
         weight: 1
         density: 1
     - model: Mohaddz/Qwen3-14B-Instruct-LoRA-1310-insta500K-Merged
       parameters:
         weight: 1
         density: 1
     - model: Qwen/Qwen3-14B
       parameters:
         weight: 1
         density: 1
   merge_method: ties
   base_model: Qwen/Qwen3-14B-Base
   parameters:
     weight: 1
     density: 1
     normalize: true
     int8_mask: true
   tokenizer_source: Qwen/Qwen3-14B
   dtype: bfloat16

```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Mohaddz/Qwen3-14B-Instruct-1310-insta500K-think-orca-TIES"
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"])
```