README.md

---
license: apache-2.0
datasets:
- fine-tuned/scidocs-c-64-24-gpt-4o-2024-05-133652
- allenai/c4
language:
- en
pipeline_tag: feature-extraction
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
- Paper
- Stationery
- Office
- Crafts
- Printing
---
This model is a fine-tuned version of [**jinaai/jina-embeddings-v2-base-en**](https://huggingface.co/jinaai/jina-embeddings-v2-base-en) designed for the following use case:

general search for paper products

## 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:

```python
from sentence_transformers import SentenceTransformer
from sentence_transformers.util import cos_sim

model = SentenceTransformer(
    'fine-tuned/scidocs-c-64-24-gpt-4o-2024-05-133652',
    trust_remote_code=True
)

embeddings = model.encode([
    'first text to embed',
    'second text to embed'
])
print(cos_sim(embeddings[0], embeddings[1]))
```