bge-m3
This repo is a mirror of embedding model bge-m3.
Information
- dimensions: 1024
- max_tokens: 8192
- language: zh, en
Example code
Install packages
pip install xinference[ggml]>=0.4.3
If you want to run with GPU acceleration, refer to installation.
Start a local instance of Xinference
xinference -p 9997
Launch and inference
from xinference.client import Client
client = Client("http://localhost:9997")
model_uid = client.launch_model(
model_name="bge-m3",
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 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.
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