Building upon the foundational models of the Qwen3 series, Qwen3 Embedding provides a comprehensive range of text embeddings models in various sizes
1.3M Pulls 12 Tags Updated 5 months ago
nomic-embed-text-v2-moe is a multilingual MoE text embedding model that excels at multilingual retrieval.
115.8K Pulls 1 Tag Updated 3 months ago
EmbeddingGemma is a 300M parameter embedding model from Google.
711.3K Pulls 5 Tags Updated 6 months ago
A high-performing open embedding model with a large token context window.
59.3M Pulls 3 Tags Updated 2 years ago
State-of-the-art large embedding model from mixedbread.ai
8.6M Pulls 4 Tags Updated 1 year ago
BGE-M3 is a new model from BAAI distinguished for its versatility in Multi-Functionality, Multi-Linguality, and Multi-Granularity.
3.6M Pulls 3 Tags Updated 1 year ago
A suite of text embedding models by Snowflake, optimized for performance.
2.5M Pulls 16 Tags Updated 1 year ago
Embedding models on very large sentence level datasets.
2.7M Pulls 10 Tags Updated 1 year ago
Sentence-transformers model that can be used for tasks like clustering or semantic search.
648.8K Pulls 3 Tags Updated 1 year ago
Snowflake's frontier embedding model. Arctic Embed 2.0 adds multilingual support without sacrificing English performance or scalability.
295.1K 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.
256.5K Pulls 6 Tags Updated 1 year ago
Embedding model from BAAI mapping texts to vectors.
224.9K Pulls 3 Tags Updated 1 year ago