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  ---
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- license: apache-2.0
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- language:
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- - en
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- pipeline_tag: feature-extraction
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  tags:
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- - code
 
 
 
 
 
 
 
 
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  ---
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-
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  <br><br>
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  <p align="center">
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- <img src="https://github.com/jina-ai/finetuner/blob/main/docs/_static/finetuner-logo-ani.svg?raw=true" alt="Finetuner logo: Finetuner helps you to create experiments in order to improve embeddings on search tasks. It accompanies you to deliver the last mile of performance-tuning for neural search applications." width="150px">
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  </p>
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  <p align="center">
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- <b>The text embedding set trained by <a href="https://jina.ai/"><b>Jina AI</b></a>, <a href="https://github.com/jina-ai/finetuner"><b>Finetuner</b></a> team.</b>
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  </p>
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  ## Intended Usage & Model Info
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  This model has 137 million parameters, which enables fast and memory efficient inference, while delivering impressive performance.
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  Additionally, we provide the following embedding models:
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- **V1 (Based on T5, 512 Seq)**
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-
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- - [`jina-embeddings-v1-small-en`](https://huggingface.co/jinaai/jina-embedding-s-en-v1): 35 million parameters.
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- - [`jina-embeddings-v1-base-en`](https://huggingface.co/jinaai/jina-embedding-b-en-v1): 110 million parameters.
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- - [`jina-embeddings-v1-large-en`](https://huggingface.co/jinaai/jina-embedding-l-en-v1): 330 million parameters.
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-
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- **V2 (Based on JinaBert, 8k Seq)**
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-
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  - [`jina-embeddings-v2-small-en`](https://huggingface.co/jinaai/jina-embeddings-v2-small-en): 33 million parameters.
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- - [`jina-embeddings-v2-base-en`](https://huggingface.co/jinaai/jina-embeddings-v2-base-en): 137 million parameters.
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- - [`jina-embeddings-v2-base-code`](https://huggingface.co/jinaai/jina-embeddings-v2-base-code): 137 million parameters **(you are here)**.
 
 
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  **<details><summary>Supported (Programming) Languages</summary>**
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  <p>
 
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  ---
 
 
 
 
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  tags:
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+ - sentence-transformers
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+ - feature-extraction
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+ - sentence-similarity
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+ - mteb
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+ datasets:
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+ - allenai/c4
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+ language: en
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+ inference: false
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+ license: apache-2.0
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  ---
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+ <!-- TODO: add evaluation results here -->
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  <br><br>
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  <p align="center">
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+ <img src="https://aeiljuispo.cloudimg.io/v7/https://cdn-uploads.huggingface.co/production/uploads/603763514de52ff951d89793/AFoybzd5lpBQXEBrQHuTt.png?w=200&h=200&f=face" alt="Finetuner logo: Finetuner helps you to create experiments in order to improve embeddings on search tasks. It accompanies you to deliver the last mile of performance-tuning for neural search applications." width="150px">
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  </p>
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  <p align="center">
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+ <b>The text embedding set trained by <a href="https://jina.ai/"><b>Jina AI</b></a>.</b>
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  </p>
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+ ## Quick Start
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+
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+ The easiest way to starting using `jina-embeddings-v2-base-en` is to use Jina AI's [Embedding API](https://jina.ai/embeddings/).
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+
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  ## Intended Usage & Model Info
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  This model has 137 million parameters, which enables fast and memory efficient inference, while delivering impressive performance.
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  Additionally, we provide the following embedding models:
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  - [`jina-embeddings-v2-small-en`](https://huggingface.co/jinaai/jina-embeddings-v2-small-en): 33 million parameters.
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+ - [`jina-embeddings-v2-base-en`](https://huggingface.co/jinaai/jina-embeddings-v2-base-en): 137 million parameters **(you are here)**.
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+ - [`jina-embeddings-v2-base-zh`](https://huggingface.co/jinaai/jina-embeddings-v2-base-zh): Chinese-English Bilingual embeddings.
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+ - [`jina-embeddings-v2-base-de`](https://huggingface.co/jinaai/jina-embeddings-v2-base-de): German-English Bilingual embeddings.
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+ - [`jina-embeddings-v2-base-es`](https://huggingface.co/jinaai/jina-embeddings-v2-base-es): Spanish-English Bilingual embeddings (soon).
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  **<details><summary>Supported (Programming) Languages</summary>**
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  <p>