This model is a fine-tuned version of jinaai/jina-embeddings-v2-base-en designed for the following use case:

Mathematics - Geometry for k-6 kids aligned with California common core standards

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 sentence_transformers import SentenceTransformer
from sentence_transformers.util import cos_sim

model = SentenceTransformer(
    'fine-tuned/jinaai_jina-embeddings-v2-base-en-6132024-wvrg-webapp',
    trust_remote_code=True
)

embeddings = model.encode([
    'first text to embed',
    'second text to embed'
])
print(cos_sim(embeddings[0], embeddings[1]))
Downloads last month
7
Safetensors
Model size
137M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Datasets used to train fine-tuned/jinaai_jina-embeddings-v2-base-en-6132024-wvrg-webapp

Spaces using fine-tuned/jinaai_jina-embeddings-v2-base-en-6132024-wvrg-webapp 2