Building upon the foundational models of the Qwen3 series, Qwen3 Embedding provides a comprehensive range of text embeddings models in various sizes
4M Pulls 12 Tags Updated 12 months ago
nomic-embed-text-v2-moe is a multilingual MoE text embedding model that excels at multilingual retrieval.
918.3K Pulls 1 Tag Updated 9 months ago
A high-performing open embedding model with a large token context window.
86.2M Pulls 3 Tags Updated 2 years ago
State-of-the-art large embedding model from mixedbread.ai
14.8M Pulls 4 Tags Updated 2 years ago
BGE-M3 is a new model from BAAI distinguished for its versatility in Multi-Functionality, Multi-Linguality, and Multi-Granularity.
6.7M Pulls 3 Tags Updated 2 years ago
EmbeddingGemma is a 300M parameter embedding model from Google.
2.1M Pulls 5 Tags Updated 1 year ago
Embedding models on very large sentence level datasets.
3.6M Pulls 10 Tags Updated 2 years ago
A suite of text embedding models by Snowflake, optimized for performance.
3.1M Pulls 16 Tags Updated 2 years ago
Sentence-transformers model that can be used for tasks like clustering or semantic search.
941.7K Pulls 3 Tags Updated 2 years ago
Snowflake's frontier embedding model. Arctic Embed 2.0 adds multilingual support without sacrificing English performance or scalability.
453.3K Pulls 3 Tags Updated 1 year ago
The IBM Granite Embedding 30M and 278M models models are text-only dense biencoder embedding models, with 30M available in English only and 278M serving multilingual use cases.
370.2K Pulls 6 Tags Updated 1 year ago
Embedding model from BAAI mapping texts to vectors.
286K Pulls 3 Tags Updated 2 years ago