BAAI:BGE-M3
baai/bge-m3
The BGE-M3 model is a multi-functional, multi-lingual, and multi-granularity text embedding framework that integrates three retrieval methods: dense retrieval, multi-vector retrieval, and sparse retrieval. Capable of processing over 100 languages and inputs ranging from short sentences to lengthy documents (up to 8,192 tokens), it delivers state-of-the-art performance in multilingual and cross-lingual tasks, topping benchmarks like MIRACL and MKQA. Additionally, BGE-M3 excels in long-document retrieval, achieving strong results on datasets such as MLDR and NarrativeQA, solidifying its versatility across diverse text granularities and applications.
价格
| 输入 | $0.01/百万 tokens |
| 输出 | $0.01/百万 tokens |
使用以下代码示例来集成我们的API：
1from openai import OpenAI
2
3client = OpenAI(
4 api_key="<Your API Key>",
5 base_url="https://api.jiekou.ai/openai"
6)
7
8response = client.chat.completions.create(
9 model="baai/bge-m3",
10 messages=[
11 {"role": "system", "content": "You are a helpful assistant."},
12 {"role": "user", "content": "Hello, how are you?"}
13 ],
14 max_tokens=96000,
15 temperature=0.7
16)
17
18print(response.choices[0].message.content)信息
提供商
量化
-
支持的功能
上下文长度
8192
最大输出
96000
Input Capabilities
text
Output Capabilities
text