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BGE-M3-Embedding-Unsupervised

Embedding modelM3

BGE-M3-Embedding-Unsupervised

Release date: 2024-01-30Updated: 2024-02-01 15:35:55.548850
Live demoGitHubHugging FaceCompare
Parameters
113M
Context length
8K
Chinese support
Supported
Reasoning ability

BGE-M3-Embedding-Unsupervised 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-Unsupervised

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-Unsupervised

Open source & experience

BGE-M3-Embedding-Unsupervised

Official resources

BGE-M3-Embedding-Unsupervised

API details

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

Benchmark Results

No benchmark data to show.

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BGE-M3-Embedding-Unsupervised

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-Unsupervised

Model Overview

BGE-M3-Embedding-Unsupervised 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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