---
title: Rombos-LLM-V2.6-Qwen-14b
canonical_url: "https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b"
md_url: "https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b.md"
repository: okwinds/Rombos-LLM-V2.6-Qwen-14b
last_updated: 2024-11-03
license: "Apache License 2.0"
pipeline_tag: text-generation
tasks:
  - text-generation
model_type:
  - qwen2
architectures:
  - Qwen2ForCausalLM
base_model:
  - Qwen/Qwen2.5-14B-Instruct
base_model_relation: finetune
parameters: 14.8B
tensor_type:
  - BF16
library_name:
  - safetensors
  - pytorch
frameworks:
  - Pytorch
language:
  - en
  - cn
inference_backends:
  - "deploy_task text/emb"
  - "lmdeploy 0.9.1"
  - "lmdeploy_turbomind 0.9.1"
  - "sglang 0.5.2"
  - "vllm 0.9.2"
downloads: 74
stars: 0
tags:
  - Chat
  - Instruct
  - fine-tuned
---

# Rombos-LLM-V2.6-Qwen-14b

> Rombos-LLM-V2.6-Qwen-14b - okwinds 在 ModelScope 开源的模型。Rombos-LLM-V2.6-Qwen-14b High-performance finetuned

okwinds/Rombos-LLM-V2.6-Qwen-14b 是 ModelScope 魔搭社区上的 14.8B 参数text-generation模型，采用 Apache License 2.0 许可，基于 Qwen/Qwen2.5-14B-Instruct 构建，可用 deploy_task text/emb、lmdeploy 0.9.1、lmdeploy_turbomind 0.9.1 部署。

- **Repository**: okwinds/Rombos-LLM-V2.6-Qwen-14b
- **License**: Apache License 2.0
- **Tasks**: text-generation
- **Parameters**: 14.8B
- **Base model**: Qwen/Qwen2.5-14B-Instruct
- **Inference backends**: deploy_task text/emb, lmdeploy 0.9.1, lmdeploy_turbomind 0.9.1, sglang 0.5.2, vllm 0.9.2
- **Tags**: Chat, Instruct, fine-tuned
- **Downloads**: 74
- **Stars**: 0
- **Last updated**: 2024-11-03

Source: https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b

---

# Rombos-LLM-V2.6-Qwen-14b High-performance finetuned

- ***同系合集 [Rombos-LLM-Qwen2.5](https://www.modelscope.cn/collections/Rombos-LLM-Qwen25-4dc8690ad7f541)***

## Download

SDK下载
```bash
#安装ModelScope
pip install modelscope
```
```python
#SDK模型下载
from modelscope import snapshot_download
model_dir = snapshot_download('okwinds/Rombos-LLM-V2.6-Qwen-14b')
```
Git下载
```
#Git模型下载
git clone https://www.modelscope.cn/okwinds/Rombos-LLM-V2.6-Qwen-14b.git
```

# 模型简介

本模型转载于 huggingface 上的 [rombodawg/Rombos-LLM-V2.6-Qwen-14b](https://huggingface.co/rombodawg/Rombos-LLM-V2.6-Qwen-14b)

作者介绍到：本模型是一个基于 [Qwen/Qwen2.5-14B](https://www.modelscope.cn/models/Qwen/Qwen2.5-14B) 的 Continuous Fine-tuning 版本，并通过 [TIES-Merging](https://ar5iv.labs.arxiv.org/html/2306.01708) 方法将合并了adapter的 [Qwen/Qwen2.5-14B-Instruct](https://www.modelscope.cn/models/qwen/qwen2.5-14b-instruct) 与 [Qwen/Qwen2.5-14B](https://www.modelscope.cn/models/Qwen/Qwen2.5-14B) 进行了 TIES Merge。这使得本模型的性能优于原始的 base 模型以及 pretrain 后 fine-tune 的 Instruct 模型。

Model tree for [okwinds/Rombos-LLM-V2.6-Qwen-14b](https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b) </br>
	&nbsp;Base model - [Qwen/Qwen2.5-14B](https://www.modelscope.cn/models/Qwen/Qwen2.5-14B) </br>
		&nbsp; <span style="font-weight: bold;">╰</span>─  Finetuned - [Qwen/Qwen2.5-14B-Instruct](https://www.modelscope.cn/models/Qwen/Qwen2.5-14B-Instruct) </br>
		&nbsp; &nbsp; &nbsp; &nbsp; <span style="font-weight: bold;">╰</span>─  Finetuned - [本模型 okwinds/Rombos-LLM-V2.6-Qwen-14b](https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b) </br>

# Benchmark

以下摘自 2024-10-29 的 Huggingface 上 [Leadboard](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) 排名数据

本模型以 14B 参数量在总榜排名第49。截图：

<img src="https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b/resolve/master/HF-Leadboard-Total-2024-10-29.png" />

在 10-32B 参数量模型中排名第7。截图：

<img src="https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b/resolve/master/HF-Leadboard-10-32B-2024-10-29.png" />

在 10-20B 参数量模型中排名第1。

<img src="https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b/resolve/master/HF-Leadboard-10-20B-2024-10-29.png" />

截图中的数据：

| **Model** |**Average️**|**IFEval**|**BBH**|**MATH Lvl 5**|**GPQA**|**MUSR**|**MMLU-PRO**|
|-|-|-|-|-|-|-|-|
|<span style="color:#ff6600">rombodawg/Rombos-LLM-V2.6-Qwen-14b</span>|35.89|52.14|49.22|28.85|17|19.26|48.85|
|rombodawg/Rombos-LLM-V2.5-Qwen-14b|34.52|58.4|49.39|15.63|16.22|18.83|48.62|
|Tsunami-th/Tsunami-1.0-14B-Instruct |34.2|78.29|49.15|0|14.21|16.34|47.21|
|tanliboy/lambda-qwen2.5-14b-dpo-test |33.52|82.31|48.45|0|14.99|12.59|42.75|
|jpacifico/Chocolatine-14B-Instruct-DPO-v1.2 |33.3|68.52|49.85|17.98|10.07|12.35|41.07|
|TheTsar1209/qwen-carpmuscle-v0.2 |33.11|52.57|48.18|25|14.09|12.75|46.08|
|microsoft/Phi-3-medium-4k-instruct |32.67|64.23|49.38|16.99|11.52|13.05|40.84|
|TheTsar1209/qwen-carpmuscle-v0.1 |32.59|56.22|48.83|21.15|12.53|10.15|46.67|
|v000000/Qwen2.5-Lumen-14B |32.2|80.64|48.51|0|10.4|10.29|43.36|
|Qwen/Qwen2.5-14B-Instruct |32.18|81.58|48.36|0|9.62|10.16|43.38|
|v000000/Qwen2.5-14B-Gutenberg-1e-Delta |32.11|80.45|48.62|0|10.51|9.38|43.67|
|internlm/internlm2_5-20b-chat |32.08|70.1|62.83|0|9.51|16.74|33.31|