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BGE-M3-Embedding

Embedding modelM3

BGE-M3-Embedding

Release date: 2024-01-30Updated: 2024-02-01 23:26:23.7451,597
Live demoGitHubHugging FaceCompare
Parameters
113M
Context length
8K
Chinese support
Supported
Reasoning ability

BGE-M3-Embedding is an AI model published by 北京智源人工智能研究院, released on 2024-01-30, for Embedding model, with 113M parameters, and 8K context length, requiring about 2.27GB storage, under the MIT License license.

Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology

BGE-M3-Embedding

Model basics

Reasoning traces
Not supported
Thinking modes
Thinking modes not supported
Context length
8K tokens
Max output length
No data
Model type
Embedding model
Modality (in / out)
Text → Embedding
Release date
2024-01-30
Model file size
2.27GB
MoE architecture
No
Total params / Active params
113M / N/A
Knowledge cutoff
No data
BGE-M3-Embedding

Open source & experience

Code license
MIT License
Weights license
MIT License- 免费商用授权
GitHub repo
https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/BGE_M3
Hugging Face
https://huggingface.co/BAAI/bge-m3
Live demo
No live demo
BGE-M3-Embedding

Official resources

BGE-M3-Embedding

API details

API speed
No data
No public API pricing yet.
BGE-M3-Embedding

Benchmark Results

No benchmark data to show.

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BGE-M3-Embedding

Publisher

北京智源人工智能研究院
北京智源人工智能研究院
View publisher details
BGE-M3-Embedding

Model Overview

BGE-M3-Embedding is an AI model published by 北京智源人工智能研究院, released on 2024-01-30, for Embedding model, with 113M parameters, and 8K context length, requiring about 2.27GB storage, under the MIT License license.

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