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The model is a fine-tuned version of jinaai/jina-embeddings-v2-base-en designed for the following use case: This model is designed to support various applications in natural language processing and understanding.

How to Use

This model can be easily integrated into your NLP pipeline for tasks such as text classification, sentiment analysis, entity recognition, and more. Here's a simple example to get you started:

from transformers import AutoModel, AutoTokenizer

llm_name = "jina-embeddings-v2-base-en-03052024-x8ew-webapp"
tokenizer = AutoTokenizer.from_pretrained(llm_name)
model = AutoModel.from_pretrained(llm_name, trust_remote_code=True)

tokens = tokenizer("Your text here", return_tensors="pt")
embedding = model(**tokens)
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Model size
137M params
Tensor type
F32
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Datasets used to train fine-tuned/jina-embeddings-v2-base-en-03052024-x8ew-webapp

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