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BGE-M3-Embedding-Unsupervised

Embedding modelM3

BGE-M3-Embedding-Unsupervised

Release date: 2024-01-30Updated: 2024-02-01 15:35:55.548857
Parameters
113M
Context length
8K
Chinese support
Supported
Reasoning ability

BGE-M3-Embedding-Unsupervised is an AI model published by Beijing Academy of Artificial Intelligence, released on 2024-01-30, for Embedding model, with 113M parameters, and 8K context length, requiring about 2.27GB storage.

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

Code license
Weights license
MIT License- Commercial use permitted
Live demo
No live demo
BGE-M3-Embedding-Unsupervised

Official resources

Paper
DataLearnerAI blog
No blog post yet
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

Beijing Academy of Artificial Intelligence
Beijing Academy of Artificial Intelligence
View publisher details
BGE-M3-Embedding-Unsupervised

Model Overview

BGE-M3-Embedding-Unsupervised is an AI model published by Beijing Academy of Artificial Intelligence, released on 2024-01-30, for Embedding model, with 113M parameters, and 8K context length, requiring about 2.27GB storage.

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