---
title: DeepSeek-V2.5-1210-quantized.w4a16
canonical_url: "https://www.modelscope.cn/models/nm-testing/DeepSeek-V2.5-1210-quantized.w4a16"
md_url: "https://www.modelscope.cn/models/nm-testing/DeepSeek-V2.5-1210-quantized.w4a16.md"
repository: nm-testing/DeepSeek-V2.5-1210-quantized.w4a16
last_updated: 2025-02-25
model_type:
  - deepseek_v2
architectures:
  - DeepseekV2ForCausalLM
parameters: 32.3B
tensor_type:
  - BF16
  - I64
  - I32
library_name:
  - safetensors
  - pytorch
frameworks:
  - pytorch
inference_backends:
  - "deploy_task text/emb"
  - "lmdeploy 0.9.1"
  - "lmdeploy_turbomind 0.9.1"
  - "sglang 0.5.2"
  - "vllm 0.9.2"
downloads: 717
stars: 0
---

# DeepSeek-V2.5-1210-quantized.w4a16

> DeepSeek-V2.5-1210-quantized.w4a16 - nm-testing 在 ModelScope 开源的模型。当前模型的贡献者未提供更加详细的模型介绍。模型文件和权重，可浏览“模型文件”页面获取。 您可以通过如下git clone命令，或者ModelScope SDK来下载模型

nm-testing/DeepSeek-V2.5-1210-quantized.w4a16 是 ModelScope 魔搭社区上的 32.3B 参数机器学习模型，可用 deploy_task text/emb、lmdeploy 0.9.1、lmdeploy_turbomind 0.9.1 部署。

- **Repository**: nm-testing/DeepSeek-V2.5-1210-quantized.w4a16
- **Parameters**: 32.3B
- **Inference backends**: deploy_task text/emb, lmdeploy 0.9.1, lmdeploy_turbomind 0.9.1, sglang 0.5.2, vllm 0.9.2
- **Downloads**: 717
- **Stars**: 0
- **Last updated**: 2025-02-25

Source: https://www.modelscope.cn/models/nm-testing/DeepSeek-V2.5-1210-quantized.w4a16

---

### 当前模型的贡献者未提供更加详细的模型介绍。模型文件和权重，可浏览“模型文件”页面获取。
#### 您可以通过如下git clone命令，或者ModelScope SDK来下载模型

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('nm-testing/DeepSeek-V2.5-1210-quantized.w4a16')
```
Git下载
```
#Git模型下载
git clone https://www.modelscope.cn/nm-testing/DeepSeek-V2.5-1210-quantized.w4a16.git
```

<p style="color: lightgrey;">如果您是本模型的贡献者，我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a>，及时完善模型卡片内容。</p>