BGE-M3
PermissiveBAAI · BGE · Released 2024-01
568MEmbedding
A versatile embedding model that unifies dense, sparse, and multi-vector (ColBERT-style) retrieval in one checkpoint across 100+ languages.
Strengths
- +MIT license, unrestricted use
- +Supports dense, sparse, and multi-vector retrieval from one model
- +8192-token context, long for an embedding model
Limitations
- -Multi-vector mode is slower and storage-heavier than plain dense embeddings
- -Larger than lightweight embedders like all-MiniLM for simple use cases
License
MIT
use commercially with attribution niceties
Hardware
runs on a good consumer GPU (or Apple Silicon) with quantization
Links
Stats
BAAI/bge-m3— downloads·— likes
via Hugging Face