---
title: Mixtral-8x7B-Instruct-v0.1-FP8-quantized
canonical_url: "https://www.modelscope.cn/models/nm-testing/Mixtral-8x7B-Instruct-v0.1-FP8-quantized"
md_url: "https://www.modelscope.cn/models/nm-testing/Mixtral-8x7B-Instruct-v0.1-FP8-quantized.md"
repository: nm-testing/Mixtral-8x7B-Instruct-v0.1-FP8-quantized
last_updated: 2026-08-24
model_type:
  - mixtral
architectures:
  - MixtralForCausalLM
parameters: 46.7B
tensor_type:
  - F8_E4M3
  - F16
library_name:
  - safetensors
  - pytorch
frameworks:
  - pytorch
downloads: 696
stars: 0
---

# Mixtral-8x7B-Instruct-v0.1-FP8-quantized

> Mixtral-8x7B-Instruct-v0.1-FP8-quantized - 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

- **Repository**: nm-testing/Mixtral-8x7B-Instruct-v0.1-FP8-quantized
- **Parameters**: 46.7B
- **Downloads**: 696
- **Stars**: 0
- **Last updated**: 2026-08-24

Source: https://www.modelscope.cn/models/nm-testing/Mixtral-8x7B-Instruct-v0.1-FP8-quantized

---

### 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/Mixtral-8x7B-Instruct-v0.1-FP8-quantized')
```
Git下载
```
#Git模型下载
git clone https://www.modelscope.cn/nm-testing/Mixtral-8x7B-Instruct-v0.1-FP8-quantized.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>