metadata
license: apache-2.0
datasets:
- fine-tuned/BAAI_bge-small-en-v1_5-18062024-56t5-webapp
- allenai/c4
language:
- en
pipeline_tag: feature-extraction
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
- Research
- Academic
- Papers
- Scholarly
- Articles
This model is a fine-tuned version of BAAI/bge-small-en-v1.5 designed for the following use case:
information retrieval system for academic research papers
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/BAAI_bge-small-en-v1_5-18062024-56t5-webapp',
trust_remote_code=True
)
embeddings = model.encode([
'first text to embed',
'second text to embed'
])
print(cos_sim(embeddings[0], embeddings[1]))