arkohut/jina-embeddings-v2-base-en

feature-extraction model by arkohut

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The text embedding set trained by Jina AI. The easiest way to starting using jina-embeddings-v2-base-en is to use Jina AI's Embedding API. jina-embeddings-v2-base-en is an English, monolingual embedding model supporting 8192 sequence length. It is based on a BERT architecture (JinaBERT) that supports the symmetric bidirectional variant of ALiBi to allow longer sequence length. The backbone jina-bert-v2-base-en is pretrained on the C4 dataset. The 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. The embedding model was trained using 512 sequence length, but extrapolates to 8k sequence length (or even longer) thanks to ALiBi. This makes our model useful for a range of use cases, especially when processing long documents is needed, including long document retrieval, semantic textual similarity, text reranking, recommendation, RAG and…

arkohut/jina-embeddings-v2-base-en on Hugging Face A short preview, not the full document.

Read the full model card ↗ · Preview checked 2026-10-31T06:59:33.315Z

Inside the original model card — Document outline
  1. Quick Start
  2. Intended Usage & Model Info
  3. Data & Parameters
  4. Usage
  5. Why mean pooling?
  6. Alternatives to Using Transformers (or SentencTransformers) Package
  7. Use Jina Embeddings for RAG
  8. Plans
  9. Trouble Shooting
  10. Contact
  11. Citation

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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

Model overview

arkohut/jina-embeddings-v2-base-en is a feature-extraction model repository published by arkohut on Hugging Face. The source reports the sentence-transformers library.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task
feature-extraction
Library
sentence-transformers
Recent downloads (30 days)
94,676
Cumulative likes
0
Hugging Face trending score
0
Reported safetensors parameters
137,368,320
Architecture
JinaBertForMaskedLM
License
apache-2.0
Access
Not gated by Hugging Face
Created
2024-11-19T17:18:48.000Z
Last modified
2024-11-19T17:20:45.000Z

Compatibility and lineage

Reported languages: en

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Model card and usage instructions

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Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:29.511Z. Daily imports are snapshots, not real-time monitoring.

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