---
title: jina-embeddings-v2-small-en
canonical_url: "https://www.modelscope.cn/models/Xorbits/jina-embeddings-v2-small-en"
md_url: "https://www.modelscope.cn/models/Xorbits/jina-embeddings-v2-small-en.md"
repository: Xorbits/jina-embeddings-v2-small-en
last_updated: 2023-11-30
license: "Apache License 2.0"
model_type:
  - bert
architectures:
  - JinaBertForMaskedLM
parameters: 32.7M
tensor_type:
  - F16
library_name:
  - onnx
  - safetensors
  - xinference
frameworks:
  - xinference
downloads: 251
stars: 0
---

# jina-embeddings-v2-small-en

> jina-embeddings-v2-small-en - Xorbits 在 ModelScope 开源的模型。jina-embeddings-v2-small-en

Xorbits/jina-embeddings-v2-small-en 是 ModelScope 魔搭社区上的 32.7M 参数机器学习模型，采用 Apache License 2.0 许可。

- **Repository**: Xorbits/jina-embeddings-v2-small-en
- **License**: Apache License 2.0
- **Parameters**: 32.7M
- **Downloads**: 251
- **Stars**: 0
- **Last updated**: 2023-11-30

Source: https://www.modelscope.cn/models/Xorbits/jina-embeddings-v2-small-en

---

## jina-embeddings-v2-small-en

This repo is a mirror of embedding model jina-embeddings-v2-small-en.

## Information
- dimensions: 512
- max_tokens: 8192
- language: zh

## Example code

### Install packages
```bash
pip install xinference[ggml]>=0.4.3
```
If you want to run with GPU acceleration, refer to [installation](https://github.com/xorbitsai/inference#installation).

###  Start a local instance of Xinference
```bash
xinference -p 9997
```

### Launch and inference
```python
from xinference.client import Client

client = Client("http://localhost:9997")
model_uid = client.launch_model(
    model_name="jina-embeddings-v2-small-en",
    model_type="embedding"
    )
model = client.get_model(model_uid)

input_text = "What is the capital of China?"
model.create_embedding(input_text)
```

### More information

[Xinference](https://github.com/xorbitsai/inference) Replace OpenAI GPT with another LLM in your app 
by changing a single line of code. Xinference gives you the freedom to use any LLM you need. 
With Xinference, you are empowered to run inference with any open-source language models, 
speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop.

<i><a href="https://join.slack.com/t/xorbitsio/shared_invite/zt-1z3zsm9ep-87yI9YZ_B79HLB2ccTq4WA">👉 Join our Slack community!</a></i>