Granite Embedding 107m multilingual Model Summary: Granite Embedding 107M Multilingual is a 107M parameter dense biencoder embedding model from the Granite Embeddings suite that can be used to generate high quality text embeddings. This model produces embedding vectors of size 384 and is trained using a combination of open source relevance pair datasets with permissive, enterprise friendly license, and IBM collected and generated datasets. This model is developed using contrastive finetuning, knowledge distillation and model merging for improved performance. Developers: Granite Embedding Team, IBM GitHub Repository: ibm granite/granite embedding models Website : Granite Docs Paper: Technical Report Release Date : December 18th, 2024 License: Apache 2.0 Supported Languages: English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese. Users may finetune Granite Embedding 107M Multilingual for languages beyond these 12 languages. Intended use: The model is designed to produce fixed length vector representations for a given text, which can be used for text similarity, retrieval, and search applications. Usage with Sentence Transformers: Th…
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