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  • snowflake-arctic-embed2

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

    embedding 568m

    152.9K  Pulls 3  Tags Updated  9 months ago

  • shaw/dmeta-embedding-zh-small-q4

    The Q4_K_M quantized version of dmeta-embedding-zh-small.

    embedding

    885  Pulls 1  Tag Updated  1 year ago

  • shaw/dmeta-embedding-zh-q4

    The Q4_K_M quantized version of dmeta-embedding-zh.

    embedding

    797  Pulls 1  Tag Updated  1 year ago

  • aligh4699/heydariAI-persian-embeddings

    This model is an Ollama version of heydariAI-persian-embeddings from Hugging Face. This is fine-tuned version of xlm-roberta-base, specifically trained on a massive corpus of Persian data to create high-quality contextual embedding for Persian usages.

    embedding

    100  Pulls 1  Tag Updated  1 month ago

  • DC1LEX/Qwen3-embedded-4b-f16

    This is the f16 GGUF version of the new Qwen3-Embedded-4b model.

    49  Pulls 1  Tag Updated  1 month ago

  • alishendi/persian-embeddings

    This model is a GGUF version of embedding model which exists in this huggingface repository: https://huggingface.co/heydariAI/persian-embeddings

    embedding

    41  Pulls 1  Tag Updated  4 weeks ago

  • twine/noinstruct-small-embedding-v0

    q8_0 version of https://huggingface.co/avsolatorio/NoInstruct-small-Embedding-v0 , all credit to that person. I just made this version as an experiment and this model seemed interesting

    embedding

    17  Pulls 1  Tag Updated  10 months ago

  • MadMind/Qwen3-Embedding-8B-GGUF-Q4_K_M

    Embedding version of hf.co/Qwen/Qwen3-Embedding-8B-GGUF:Q4_K_M

    tools

    209  Pulls 1  Tag Updated  2 months ago

  • DC1LEX/Qwen3-Embedding-8B-f16

    This is the f16 GGUF version of the new Qwen3-Embedded-8B model.

    162  Pulls 1  Tag Updated  1 month ago

  • DC1LEX/Qwen3-Embedding-0.6B-f16

    This is the f16 GGUF version of the new Qwen3-Embedded-0.6B model.

    89  Pulls 1  Tag Updated  1 month ago

  • oscardp96/medcpt-query

    MedCPT generates embeddings of biomedical texts that can be used for semantic search (dense retrieval). Compute the embeddings of short texts (e.g., questions, search queries, sentences).

    embedding

    47  Pulls 1  Tag Updated  5 months ago

  • jina/jina-embeddings-v2-base-de

    Text embedding model (base) for English and German input of size up to 8192 tokens

    embedding

    159.2K  Pulls 1  Tag Updated  1 year ago

  • avr/sfr-embedding-mistral

    An embedding model created by Salesforce Research that you can use for semantic search. Currently the best open source embedding model on MTEB.

    29.3K  Pulls 4  Tags Updated  1 year ago

  • joanfm/jina-embeddings-v2-base-de

    Text embedding model (base) for English and German input of size up to 8192 tokens

    embedding

    413  Pulls 1  Tag Updated  1 year ago

  • milkey/gte

    General Text Embeddings (GTE) model. Towards General Text Embeddings with Multi-stage Contrastive Learning trained by Alibaba DAMO Academy.

    embedding

    2,433  Pulls 2  Tags Updated  1 year ago

  • ALIENTELLIGENCE/embeddedsystemsengineer

    AI Embedded Systems Engineer

    tools

    76  Pulls 1  Tag Updated  1 year ago

  • sam860/granite-embedding-english

    Embedding models for English language, made by the IBM-Granite team, in 2 (small) sizes

    embedding

    65  Pulls 4  Tags Updated  8 months ago

  • oscardp96/medcpt-article

    MedCPT generates embeddings of biomedical texts that can be used for semantic search (dense retrieval). Compute the embeddings of articles (e.g., PubMed titles & abstracts).

    embedding

    52  Pulls 1  Tag Updated  5 months ago

  • sam860/granite-embedding-multilingual

    Embedding models supporting multiple languages, made by the IBM-Granite team, in 2 (small) sizes

    embedding

    459  Pulls 4  Tags Updated  8 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...

    tools thinking

    20.2K  Pulls 2  Tags Updated  2 months ago

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