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  • embeddinggemma

    EmbeddingGemma is a 300M parameter embedding model from Google.

    embedding 300m

    495.6K  Pulls 5  Tags Updated  5 months ago

  • qwen3-embedding

    Building upon the foundational models of the Qwen3 series, Qwen3 Embedding provides a comprehensive range of text embeddings models in various sizes

    embedding 0.6b 4b 8b

    613.8K  Pulls 12  Tags Updated  4 months ago

  • nomic-embed-text-v2-moe

    nomic-embed-text-v2-moe is a multilingual MoE text embedding model that excels at multilingual retrieval.

    embedding

    34.2K  Pulls 1  Tag Updated  2 months ago

  • nomic-embed-text

    A high-performing open embedding model with a large token context window.

    embedding

    53.8M  Pulls 3  Tags Updated  1 year ago

  • mxbai-embed-large

    State-of-the-art large embedding model from mixedbread.ai

    embedding 335m

    7.3M  Pulls 4  Tags Updated  1 year ago

  • snowflake-arctic-embed

    A suite of text embedding models by Snowflake, optimized for performance.

    embedding 22m 33m 110m 137m 335m

    1.9M  Pulls 16  Tags Updated  1 year ago

  • snowflake-arctic-embed2

    Snowflake's frontier embedding model. Arctic Embed 2.0 adds multilingual support without sacrificing English performance or scalability.

    embedding 568m

    243.1K  Pulls 3  Tags Updated  1 year ago

  • granite-embedding

    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.

    embedding 30m 278m

    199K  Pulls 6  Tags Updated  1 year ago

  • all-minilm

    Embedding models on very large sentence level datasets.

    embedding 22m 33m

    2.4M  Pulls 10  Tags Updated  1 year ago

  • bge-large

    Embedding model from BAAI mapping texts to vectors.

    embedding 335m

    192.5K  Pulls 3  Tags Updated  1 year ago

  • exaone3.5

    EXAONE 3.5 is a collection of instruction-tuned bilingual (English and Korean) generative models ranging from 2.4B to 32B parameters, developed and released by LG AI Research.

    2.4b 7.8b 32b

    238.3K  Pulls 13  Tags Updated  1 year ago

  • aksh-desai/qwen3-vl-embedding

    49  Pulls 6  Tags Updated  3 days ago

  • MedAIBase/Ling-flash-2.0

    Ling-flash-2.0, a language model with 100B total parameters and 6.1B activated parameters (4.8B non-embedding).

    100b

    42  Pulls 2  Tags Updated  3 weeks ago

  • AntAngelMed/Ling-flash-2.0

    Ling-flash-2.0, a language model with 100B total parameters and 6.1B activated parameters (4.8B non-embedding).

    100b

    28  Pulls 2  Tags Updated  3 weeks ago

  • ibm/granite-embedding

    embedding 30m 107m 125m 278m

    1,448  Pulls 16  Tags Updated  5 months ago

  • ryanshillington/Qwen3-Embedding-4B

    This is the Qwen3 4B embedding model from here: https://huggingface.co/Qwen/Qwen3-Embedding-4B

    embedding

    909  Pulls 1  Tag Updated  5 months ago

  • ryanshillington/Qwen3-Embedding-0.6B

    This is the Qwen3 0.6B embedding model from here: https://huggingface.co/Qwen/Qwen3-Embedding-0.6B

    embedding

    878  Pulls 1  Tag Updated  5 months ago

  • k----n/jina-embeddings-v4-text-retrieval-F16

    332  Pulls 1  Tag Updated  5 months ago

  • dengcao/Qwen3-Embedding-0.6B

    Alibaba's text embedding model.Qwen3-Embedding-0.6B has the following features: Model Type: Text Embedding Supported Languages: 100+ Languages Number of Paramaters: 0.6B Context Length: 32k Embedding Dimension: Up to 1024, supports user-defined output...

    embedding

    36.8K  Pulls 2  Tags Updated  4 months ago

  • dengcao/Qwen3-Embedding-8B

    Alibaba's text embedding model.Qwen3-Embedding-8B has the following features: Model Type: Text Embedding Supported Languages: 100+ Languages Number of Paramaters: 8B Context Length: 32k Embedding Dimension: Up to 4096, supports user-defined output...

    embedding tools thinking

    32.9K  Pulls 4  Tags Updated  4 months ago

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