Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
Jina Embeddings v2 Small - en (Depr)
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Text embedding model (small) for input of size up to 8192 tokens
Product Overview
Jina Embeddings v2 Small model is optimized for speed of inference and memory efficiency - For higher accuracy, use the Base model. jina-embeddings-v2-small-en is an open-source English embedding model supporting 8192 sequence length. This state-of-the-art AI embedding model enables many applications, such as document clustering, classification, content personalization, vector search, or retrieval augmented generation.
Key Data
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Type
Model Package
Highlights
Use-cases: Vector search, retrieval augmented generation, long document clustering, sentiment analysis.
Extended context length: This model uniquely support an 8K context length, enabling them to process and understand larger chunks of data in a single pass, resulting in richer embeddings and more accurate predictions.
Model size: 32.7M parameters.
High performance over tasks across the board: Our model ranks amongst the top performing ones on HuggingFace’s MTEB leaderboard for embedding models - especially considering its small size and extended context length.
The backbone of this model was pretrained on the C4 dataset. This model is further trained on Jina AI's collection of more than 400 millions of sentence pairs and hard negatives. These pairs were obtained from various domains and were carefully selected through a thorough cleaning process.
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Usage Information
Model input and output details
Input
Summary
The model accepts JSON inputs. Texts must be passed in the following format.
{ "data": [ {"text": "How is the weather today?"}, {"text": "What is the weather like today?"}, {"text": "What's the color of an orange?"} ] }
Input MIME type
text/csv, application/jsonSample input data
Output
Summary
A JSON object with an array of IDs and Embeddings
Output MIME type
application/jsonSample output data
Sample notebook
Additional Resources
End User License Agreement
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Support Information
Jina Embeddings v2 Small - en (Depr)
We offer support through Jina AI enterprise support team.
AWS Infrastructure
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This product is offered for free. If there are any questions, please contact us for further clarifications.
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